SlideShare a Scribd company logo
1 of 63
Cochrane UK & Ireland
Symposium 2016,
Birmingham, UK, 2016-03-16
Automated Extraction of
Knowledge from Biomedical
Literature
Peter Murray-Rust1,2
[1]University of Cambridge
[2]TheContentMine
pm286 AT cam DOT ac DOT uk
Simple, Universal,
Knowledge creation and re-use
Our tools and minds are Open.
How can we help Cochrane?
Overview
Content Mining:
• Why we need it
• What it is
• How WE can do it
• The next steps
• PM-R has worked in Glaxo Group Research on drug discovery, with
WHO on adverse events and ICD-10, FDA on NDAs, EPO on patents,
etc.
The Right to Read is the Right to Mine**PeterMurray-Rust, 2011
http://contentmine.org
Not-for-private Profit
My European Heroes
Young People(ContentMine)
NEELIE KROES
Output of scholarly publishing
[2] https://en.wikipedia.org/wiki/Mont_Blanc#/media/File:Mont_Blanc_depuis_Valmorel.jpg
586,364 Crossref DOIs 201507 [1] per month
1.5 million (papers + supplemental data) /year [citation needed]*
each 3 mm thick
 4500 m high per year [2]
* Most is not Publicly readable
[1] http://www.crossref.org/01company/crossref_indicators.html
Scientific and Medical publication (STM)[+]
• World Citizens pay $450,000,000,000…
• … for research in 1,500,000 articles …
• … cost $300,000 each to create …
• … $7000 each to “publish” [*]…
• … $10,000,000,000 from academic libraries …
• … to “publishers” who forbid access to 99.9% of citizens of
the world …
• 85% of medical research is wasted (not published, badly
conceived, duplicated, …) [Lancet 2009]
[+] Figures probably +- 50 %
[*] arXiV preprint server costs $7 USD per paper
http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about-
ebola.html
We were stunned recently when we stumbled across an article by European
researchers in Annals of Virology [1982]: “The results seem to indicate that
Liberia has to be included in the Ebola virus endemic zone.” In the future,
the authors asserted, “medical personnel in Liberian health centers should be
aware of the possibility that they may come across active cases and thus be
prepared to avoid nosocomial epidemics,” referring to hospital-acquired
infection.
Adage in public health: “The road to inaction is paved with research
papers.”
Bernice Dahn (chief medical officer of Liberia’s Ministry of Health)
Vera Mussah (director of county health services)
Cameron Nutt (Ebola response adviser to Partners in Health)
A System Failure of Scholarly Publishing
CLOSED ACCESS
MEANS PEOPLE DIE
WE pay for scholarly
publications that WE
can’t read
[1] The Military-Industrial-Academic complex (1961)
(Dwight D Eisenhower, US President)
Publishers Academia
Glory+?
$$, MS
review
Taxpayer
Student
Researcher
$$ $$
in-kind
The Publisher-Academic complex[1]
Elsevier wants to control Open Data
[asked by Michelle Brook]
Prof. Ian Hargreaves (2011): "David Cameron's
exam question”: "Could it be true that laws
designed more than three centuries ago with the
express purpose of creating economic incentives
for innovation by protecting creators' rights are
today obstructing innovation and economic
growth?”
“yes. We have found that the UK's intellectual
property framework, especially with regard to
copyright, is falling behind what is needed.” "Digital
Opportunity" by Prof Ian Hargreaves - http://www.ipo.gov.uk/ipreview.htm. Licensed under CC BY 3.0 via Wikipedia -
https://en.wikipedia.org/wiki/File:Digital_Opportunity.jpg#/media/File:Digital_Opportunity.jpg
Resources
• Europe PubMedCentral http://europepmc.org/
• ContentMine toolkit https://github.com/ContentMine/
• Wikidata:
https://www.wikidata.org/wiki/Wikidata:Main_Page
• Hypothes.is https://hypothes.is/ [1]
• Etherpad: http://pads.cottagelabs.com/p/cochrane2016
• Note: early adopters can obtain our (Open) software and
run it at home…
• [1] Not used in CochraneBham workshop
Europe PubMedCentral
catalogue
getpapers
query
Daily
Crawl
EPMC, arXiv
CORE , HAL,
(UNIV repos)
ToC
services
PDF HTML
DOC ePUB
TeX XML
PNG
EPS CSV
XLSURLs
DOIs
crawl
quickscrape
norma
Normalizer
Structurer
Semantic
Tagger
Text
Data
Figures
ami
UNIV
Repos
search
Lookup
CONTENT
MINING
Chem
Phylo
Trials
Crystal
Plants
COMMUNITY
plugins
Visualization
and Analysis
PloSONE, BMC,
peerJ… Nature, IEEE,
Elsevier…
Publisher Sites
scrapers
queries
taggers
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
30, 000 pages/day
Semantic ScholarlyHTML
Facts
CONTENTMINE Complete OPEN Platform for Mining Scientific Literature
dictionaries
Dictionaries!
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
Dict A
Dict B
Image
Caption
Table
Caption
MINING
with sections
and dictionaries
[W3C Annotation / https://hypothes.is/ ]
How does Rat find knowledge
Demo
PMR runs getpapers and ami
Chris runs Python visualization of drug co-occurrence
I want to see a DEMO
Let’s try
ChemicalTagger!
http://chemicaltagger.ch.cam.ac.uk/
• Typical
Typical chemical synthesis
Open Content Mining of FACTs
Machines can interpret chemical reactions
We have done 500,000 patents. There are >
3,000,000 reactions/year. Added value > 1B Eur.
Dictionaries
• Simplest approach to knowledge extraction
and management.
We’d love to help integrate your dictionaries and
Open authorities
Disease Dictionary (ICD-10)
<dictionary title="disease">
<entry term="1p36 deletion syndrome"/>
<entry term="1q21.1 deletion syndrome"/>
<entry term="1q21.1 duplication syndrome"/>
<entry term="3-methylglutaconic aciduria"/>
<entry term="3mc syndrome”
<entry term="corpus luteum cyst”/>
<entry term="cortical blindness" />
SELECT DISTINCT ?thingLabel WHERE {
?thing wdt:P494 ?wd .
?thing wdt:P279 wd:Q12136 .
SERVICE wikibase:label {
bd:serviceParam wikibase:language "en" }
}
wdt:P494 = ICD-10 (P494) identifier
wd:Q12136 = disease (Q12136) abnormal condition that
affects the body of an organism
Wikidata ontology for disease
• ChEBI (chemicals at EBI)
ftp://ftp.ebi.ac.uk/pub/databases/chebi/Flat_file_tab_delimited/names_3star.tsv.gz)
• combined with WIKIDATA: World Health Organisation International Nonproprietary Name
(P2275)
* => 4947 items in the dictionary (inn.xml)
DRUGS
<dictionary title="inn">
<entry term="(r)-fenfluramine"/>
<entry term="abacavir"/>
<entry term="abafungin"/>
<entry term="abafungina"/>
<entry term="abafungine"/>
<entry term="abafunginum"/>
<entry term="abamectin"/>
<entry term="abarelix"/>
<entry term="abatacept"/>
<dictionary title="funders">
<!— from http://help.crossref.org/funder-registry with
thanks -->
<entry id="http://dx.doi.org/10.13039/100001436"
term="1675 Foundation"/>
<entry id="http://dx.doi.org/10.13039/100004343"
term="3M"/>
<entry id=“http://dx.doi.org/10.13039/501100005957”
term="8020 Promotion Foundation"/>
<entry id="http://dx.doi.org/10.13039/501100007139"
term="A Richer Life Foundation"/>
<entry id="http://dx.doi.org/10.13039/100006543"
term="A World Celiac Community Foundation"/>
<entry id="http://dx.doi.org/10.13039/100001962"
term="A-T Children's Project"/>
<entry id="http://dx.doi.org/10.13039/100008456"
term="A. Alfred Taubman Medical Research Institute"/>
11566 entries
Funders Dictionary
Dengue Mosquito
<dictionary name="genus">
<entry term="Aa"/>
<entry term="Aaaba"/>
<entry term="Aacanthocnema"/>
<entry term="Aaosphaeria"/>
<entry term="Aaptos"/>
<entry term="Aaptosyax"/>
<entry term="Aaroniella"/>
<entry term="Aaronsohnia"/>
<entry term="Abablemma"/>
Genera from NCBI TaxDump
<dictionary title="hgnc">
<entry term="A1BG" name="alpha-1-B glycoprotein"/>
<entry term="A1BG-AS1" name="A1BG antisense RNA 1"/>
<entry term="A1CF"
name="APOBEC1 complementation factor"/>
<entry term="A2M" name="alpha-2-macroglobulin"/>
<entry term="A2M-AS1"
name="A2M antisense RNA 1 (head to head)"/>
<entry term="A2ML1" name="alpha-2-macroglobulin-like 1"/>
<entry term="A2ML1-AS1" name="A2ML1 antisense RNA 1"/>
Human Genes (HGNC)
<entry term="Aaas"
name="achalasia, adrenocortical insufficiency, alacrimia"/>
<entry term="Aacs" name="acetoacetyl-CoA synthetase"/>
<entry term="Aadac"
name="arylacetamide deacetylase (esterase)"/>
<entry term="Aadacl2"
name="arylacetamide deacetylase-like 2"/>
<entry term="Aadacl3"
name="arylacetamide deacetylase-like 3"/>
<entry term="Aadat" name="aminoadipate aminotransferase"/>
<entry term="Aaed1"
name="AhpC/TSA antioxidant enzyme domain containing 1"/>
<entry term="Aagab"
name="alpha- and gamma-adaptin binding protein"/>
<entry term="Aak1" name="AP2 associated kinase 1"/>
<entry term="Aamdc"
name="adipogenesis associated Mth938 domain containing"/>
<entry term="Aamp"
name="angio-associated migratory protein"/>
Mouse genes (JAXson)
Ebola!
<dictionary title="tropicalVirus">
<entry term="ZIKV" name="Zika virus"/>
<entry term="Zika" name="Zika virus"/>
<entry term="DENV" name="Dengue virus"/>
<entry term="Dengue" name="Dengue virus"/>
<entry term="CHIKV" name="Chikungunya virus"/>
<entry term="Chikungunya" name="Chikungunya virus"/>
<entry term="WNV" name="West Nile virus"/>
<entry term="West Nile" name="West Nile virus"/>
<entry term="YFV" name="Yellow fever virus"/>
<entry term="Yellow fever" name="Yellow fever virus"/>
<entry term="HPV" name="Human papilloma virus"/>
<entry term="Human papilloma virus"
name="Human papilloma virus"/>
</dictionary>
Terms co-ocurring with “Zika”
<dictionary title="cochrane">
<entry term="Cochrane Library"/>
<entry term="Cochrane Reviews"/>
<entry
term="Cochrane Central Register of Controlled Trials"/>
<entry term="Cochrane"/>
<entry term="randomize"/>
<entry term="meta-analysis"/>
<entry term="Embase"/>
<entry term="MEDLINE"/>
<entry term="eligibility"/>
<entry term="exclusion"/>
<entry term="outcome"/>
<entry term="Review Manager"/>
<entry term="STATA"/>
<entry term="RCT"/>
</dictionary>
Terms lexically related to “meta-analysis”
Mining strategy
• Discover. negotiate permissions . => bibliography
• Crawl / Scrape (download), documents AND
supplemental
• Normalize. PDF => XML
• Index: facets => Facts and snippets (“entities”)
• Interpret/analyze entities => relationships,
aggregations (“Transformative”)
• Publish
catalogue
getpapers
query
Daily
Crawl
EuPMC, arXiv
CORE , HAL,
(UNIV repos)
ToC
services
PDF HTML
DOC ePUB
TeX XML
PNG
EPS CSV
XLSURLs
DOIs
crawl
quickscrape
norma
Normalizer
Structurer
Semantic
Tagger
Text
Data
Figures
ami
UNIV
Repos
search
Lookup
CONTENT
MINING
Chem
Phylo
Trials
Crystal
Plants
COMMUNITY
plugins
Visualization
and Analysis
PloSONE, BMC,
peerJ… Nature, IEEE,
Elsevier…
Publisher Sites
scrapers
queries
taggers
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
30, 000 pages/day
Semantic ScholarlyHTML
Facts
CONTENTMINE Complete OPEN Platform for Mining Scientific Literature
Precision / Recall
Systematic Reviews
Can we:
• eliminate true negatives automatically?
• extract data from formulaic language?
• mine diagrams?
• Annotate existing sources?
• forward-reference clinical trials?
Polly has 20 seconds to read this paper…
…and 10,000 more
ContentMine software can do this in a few minutes
Polly: “there were 10,000 abstracts and due
to time pressures, we split this between 6
researchers. It took about 2-3 days of work
(working only on this) to get through
~1,600 papers each. So, at a minimum this
equates to 12 days of full-time work (and
would normally be done over several weeks
under normal time pressures).”
400,000 Clinical Trials
In 10 government registries
Mapping trials => papers
http://www.trialsjournal.com/content/16/1/80
2009 => 2015. What’s
happened in last 6 years??
Search the whole scientific literature
For “2009-0100068-41”
What is “Content”?
http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.01113
03&representation=PDF CC-BY
SECTIONS
MAPS
TABLES
CHEMISTRY
TEXT
MATH
contentmine.org tackles these
Diagram Mining
Examples of plots
Multisegment diagram
But we can now
turn PDFs into
Science
We can’t turn a hamburger into a cow
Pixel => Path => Shape => Char => Word => Para => Document => SCIENCE
UNITS
TICKS
QUANTITY
SCALE
TITLES
DATA!!
2000+ points
Dumb PDF
CSV
Semantic
Spectrum
2nd Derivative
Smoothing
Gaussian Filter
Automatic
extraction
Multisegment diagram
Whitespace
“corridors”
Superpixel
Bounding box
Semantic
labels
Ln Bacterial load per fly
11.5
11.0
10.5
10.0
9.5
9.0
6.5
6.0
Days post—infection
0 1 2 3 4 5
Bitmap Image and Tesseract OCR
“Root”
OCR (Tesseract)
Norma (imageanalysis)
(((((Pyramidobacter_piscolens:195,Jonquetella_anthropi:135):86,Synergistes_jonesii:301):131,Thermotoga
_maritime:357):12,(Mycobacterium_tuberculosis:223,Bifidobacterium_longum:333):158):10,((Optiutus_te
rrae:441,(((Borrelia_burgdorferi:…202):91):22):32,(Proprinogenum_modestus:124,Fusobacterium_nucleat
um:167):217):11):9);
Semantic re-usable/computable output (ca 4 secs/image)
Politics
@Senficon (Julia Reda) :Text & Data mining in times of
#copyright maximalism:
"Elsevier stopped me doing my research"
http://onsnetwork.org/chartgerink/2015/11/16/elsevi
er-stopped-me-doing-my-research/ … #opencon #TDM
Elsevier stopped me doing my research
Chris Hartgerink
I am a statistician interested in detecting potentially problematic research such as data fabrication,
which results in unreliable findings and can harm policy-making, confound funding decisions, and
hampers research progress.
To this end, I am content mining results reported in the psychology literature. Content mining the
literature is a valuable avenue of investigating research questions with innovative methods. For
example, our research group has written an automated program to mine research papers for errors in
the reported results and found that 1/8 papers (of 30,000) contains at least one result that could
directly influence the substantive conclusion [1].
In new research, I am trying to extract test results, figures, tables, and other information reported in
papers throughout the majority of the psychology literature. As such, I need the research papers
published in psychology that I can mine for these data. To this end, I started ‘bulk’ downloading research
papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account
potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention
to redistribute the downloaded materials, had legal access to them because my university pays a
subscription, and I only wanted to extract facts from these papers.
Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days.
This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day.
Approximately two weeks after I started downloading psychology research papers, Elsevier notified my
university that this was a violation of the access contract, that this could be considered stealing of
content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading
(which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university.
I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly
hampering me in my research.
[1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The
prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods, 1–22.
doi: 10.3758/s13428-015-0664-2
Chris Hartgerink’s blog post
WILEY … “new security feature… to prevent systematic download of content
“[limit of] 100 papers per day”
“essential security feature … to protect both parties (sic)”
CAPTCHA
User has to type words
http://onsnetwork.org/chartgerink/2016/02/23/wiley-also-stopped-my-doing-my-research/
Wiley also stopped me (Chris Hartgerink) doing my research
In November, I wrote about how Elsevier wanted me to stop downloading scientific articles for my research. Today, Wiley
also ordered me to stop downloading.
As a quick recapitulation: I am a statistician doing research into detecting
potentially problematic research such as data fabrication and
estimating how often it occurs. For this, I need to download many scientific articles, because my research
applies content mining methods that extract facts from them (e.g., test statistics). These facts serve as my data to answer my research
questions. If I cannot download these research articles, I cannot collect the data I need to do my research.
I was downloading psychology research articles from the Wiley library, with a maximum of 5 per minute. I did this using the tool quickscrape,
developed by the ContentMine organization. With this, I have downloaded approximately 18,680 research articles from the Wiley library,
which I was downloading solely for research purposes.
Wiley noticed my downloading and notified my university library that they detected a compromised proxy, which they
had immediately restricted. They called it “illegally downloading copyrighted content
licensed by your institution”. However, at no point was there any investigation into whether my user credentials were
actually compromised (they were not). Whether I had legitimate reasons to download these articles was never discussed.
The original email from Wiley is available here.
As a result of Wiley denying me to download these research articles, I cannot collect data from
another one of the big publishers, alongside Elsevier. Wiley is more strict than Elsevier by immediately condemning the
downloading as illegal, whereas Elsevier offers an (inadequate) API with additional terms of use (while legitimate access
has already been obtained). I am really confused about what the publisher’s stance on content mining is, because Sage
and Springer seemingly allow it; I have downloaded 150,210 research articles from Springer
and 12,971 from Sage and they never complained about it.
ContentMine can Offer
• Collaboration
• Prototyping. YOU design the rules and system
• Rapid knowledge creation and analysis tools accessible to
EVERYONE and controlled by ANYONE.
• Access to ALL daily scientific/medical FACTs
ContentMine needs
• Joint projects with narratives
• Support in kind (code, content) and cash.
• http://contentmine.org
ContentMine can Offer
• Collaboration
• Prototyping
• Rapid knowledge creation and analysis tools accessible to
EVERYONE and controlled by ANYONE.
• Access to ALL daily scientific/medical FACTs
ContentMine needs
• Joint projects with narratives
• Support in kind (code, content) and cash.
• http://contentmine.org
KNOWLEDGE
SAVES
LIVES

More Related Content

What's hot

Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016 Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016 TheContentMine
 
Can Computers understand the scientific literature (includes compscie material)
Can Computers understand the scientific literature (includes compscie material)Can Computers understand the scientific literature (includes compscie material)
Can Computers understand the scientific literature (includes compscie material)TheContentMine
 
Content Mining of Science in Cambridge
Content Mining of Science in CambridgeContent Mining of Science in Cambridge
Content Mining of Science in CambridgeTheContentMine
 
Digital Scholarship: Enlightenment or Devastated Landscape?
Digital Scholarship: Enlightenment or Devastated Landscape? Digital Scholarship: Enlightenment or Devastated Landscape?
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
 
High throughput mining of the scholarly literature
High throughput mining of the scholarly literature High throughput mining of the scholarly literature
High throughput mining of the scholarly literature TheContentMine
 
Amanuens.is HUmans and machines annotating scholarly literature
Amanuens.is HUmans and machines annotating scholarly literature Amanuens.is HUmans and machines annotating scholarly literature
Amanuens.is HUmans and machines annotating scholarly literature TheContentMine
 
ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika! ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika! TheContentMine
 
ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika!ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika!petermurrayrust
 
The culture of researchData
The culture of researchData The culture of researchData
The culture of researchData TheContentMine
 
Content Mining of Science and Medicine
Content Mining of Science and MedicineContent Mining of Science and Medicine
Content Mining of Science and MedicineTheContentMine
 
ContentMine (TDM) at JISC Digifest
ContentMine (TDM) at JISC DigifestContentMine (TDM) at JISC Digifest
ContentMine (TDM) at JISC Digifestpetermurrayrust
 
Content Mining of Science in Europe
Content Mining of Science in EuropeContent Mining of Science in Europe
Content Mining of Science in Europepetermurrayrust
 
Automatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and  Medicine from the scholarly literatureAutomatic Extraction of Science and  Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literaturepetermurrayrust
 
Mining the scientific literature for plants and chemistry
Mining the scientific literature for plants and chemistryMining the scientific literature for plants and chemistry
Mining the scientific literature for plants and chemistrypetermurrayrust
 
Text and Data Mining explained at FTDM
Text and Data Mining explained at FTDMText and Data Mining explained at FTDM
Text and Data Mining explained at FTDMpetermurrayrust
 
High throughput mining of the scholarly literature; talk at NIH
High throughput mining of the scholarly literature; talk at NIHHigh throughput mining of the scholarly literature; talk at NIH
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
 
Biovision2017 Accessing the scientific literature
Biovision2017 Accessing the scientific literatureBiovision2017 Accessing the scientific literature
Biovision2017 Accessing the scientific literaturepetermurrayrust
 
Content Mining at Wellcome Trust
Content Mining at Wellcome TrustContent Mining at Wellcome Trust
Content Mining at Wellcome Trustpetermurrayrust
 
ContentMine: Mining the Scientific Literature
ContentMine: Mining the Scientific LiteratureContentMine: Mining the Scientific Literature
ContentMine: Mining the Scientific Literaturepetermurrayrust
 

What's hot (20)

Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016 Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016
 
Can Computers understand the scientific literature (includes compscie material)
Can Computers understand the scientific literature (includes compscie material)Can Computers understand the scientific literature (includes compscie material)
Can Computers understand the scientific literature (includes compscie material)
 
Content Mining of Science in Cambridge
Content Mining of Science in CambridgeContent Mining of Science in Cambridge
Content Mining of Science in Cambridge
 
Digital Scholarship: Enlightenment or Devastated Landscape?
Digital Scholarship: Enlightenment or Devastated Landscape? Digital Scholarship: Enlightenment or Devastated Landscape?
Digital Scholarship: Enlightenment or Devastated Landscape?
 
High throughput mining of the scholarly literature
High throughput mining of the scholarly literature High throughput mining of the scholarly literature
High throughput mining of the scholarly literature
 
Cochrane workshop2016
Cochrane workshop2016Cochrane workshop2016
Cochrane workshop2016
 
Amanuens.is HUmans and machines annotating scholarly literature
Amanuens.is HUmans and machines annotating scholarly literature Amanuens.is HUmans and machines annotating scholarly literature
Amanuens.is HUmans and machines annotating scholarly literature
 
ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika! ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika!
 
ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika!ContentMine + EPMC: Finding Zika!
ContentMine + EPMC: Finding Zika!
 
The culture of researchData
The culture of researchData The culture of researchData
The culture of researchData
 
Content Mining of Science and Medicine
Content Mining of Science and MedicineContent Mining of Science and Medicine
Content Mining of Science and Medicine
 
ContentMine (TDM) at JISC Digifest
ContentMine (TDM) at JISC DigifestContentMine (TDM) at JISC Digifest
ContentMine (TDM) at JISC Digifest
 
Content Mining of Science in Europe
Content Mining of Science in EuropeContent Mining of Science in Europe
Content Mining of Science in Europe
 
Automatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and  Medicine from the scholarly literatureAutomatic Extraction of Science and  Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literature
 
Mining the scientific literature for plants and chemistry
Mining the scientific literature for plants and chemistryMining the scientific literature for plants and chemistry
Mining the scientific literature for plants and chemistry
 
Text and Data Mining explained at FTDM
Text and Data Mining explained at FTDMText and Data Mining explained at FTDM
Text and Data Mining explained at FTDM
 
High throughput mining of the scholarly literature; talk at NIH
High throughput mining of the scholarly literature; talk at NIHHigh throughput mining of the scholarly literature; talk at NIH
High throughput mining of the scholarly literature; talk at NIH
 
Biovision2017 Accessing the scientific literature
Biovision2017 Accessing the scientific literatureBiovision2017 Accessing the scientific literature
Biovision2017 Accessing the scientific literature
 
Content Mining at Wellcome Trust
Content Mining at Wellcome TrustContent Mining at Wellcome Trust
Content Mining at Wellcome Trust
 
ContentMine: Mining the Scientific Literature
ContentMine: Mining the Scientific LiteratureContentMine: Mining the Scientific Literature
ContentMine: Mining the Scientific Literature
 

Viewers also liked

Mining Scientific Diagrams for facts
Mining Scientific Diagrams for facts Mining Scientific Diagrams for facts
Mining Scientific Diagrams for facts TheContentMine
 
Open Data and Open Science
Open Data and Open ScienceOpen Data and Open Science
Open Data and Open ScienceTheContentMine
 
Mining Scientific Images
Mining Scientific ImagesMining Scientific Images
Mining Scientific ImagesTheContentMine
 
OpenNotebookScience NOW!
OpenNotebookScience NOW!OpenNotebookScience NOW!
OpenNotebookScience NOW!TheContentMine
 
ContentMine and WikiData
ContentMine and WikiDataContentMine and WikiData
ContentMine and WikiDataTheContentMine
 

Viewers also liked (6)

Mining Scientific Diagrams for facts
Mining Scientific Diagrams for facts Mining Scientific Diagrams for facts
Mining Scientific Diagrams for facts
 
Open Data and Open Science
Open Data and Open ScienceOpen Data and Open Science
Open Data and Open Science
 
Making Theses USEFUL
Making Theses USEFULMaking Theses USEFUL
Making Theses USEFUL
 
Mining Scientific Images
Mining Scientific ImagesMining Scientific Images
Mining Scientific Images
 
OpenNotebookScience NOW!
OpenNotebookScience NOW!OpenNotebookScience NOW!
OpenNotebookScience NOW!
 
ContentMine and WikiData
ContentMine and WikiDataContentMine and WikiData
ContentMine and WikiData
 

Similar to Automated Extraction of Knowledge from Biomedical Literature

ContentMining for France and Europe; Lessons from 2 years in UK
ContentMining for France and Europe; Lessons from 2 years in UKContentMining for France and Europe; Lessons from 2 years in UK
ContentMining for France and Europe; Lessons from 2 years in UKpetermurrayrust
 
WikiFactMine: Science for Everyone
WikiFactMine: Science for EveryoneWikiFactMine: Science for Everyone
WikiFactMine: Science for Everyonepetermurrayrust
 
Cohg presentation for drf day
Cohg presentation for drf dayCohg presentation for drf day
Cohg presentation for drf dayAnne Littlewood
 
Why ContentMining is useful
Why ContentMining is usefulWhy ContentMining is useful
Why ContentMining is usefulTheContentMine
 
Why ContentMining is useful
Why ContentMining is usefulWhy ContentMining is useful
Why ContentMining is usefulpetermurrayrust
 
Automatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literatureAutomatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literatureTheContentMine
 
Towards Responsible Content Mining: A Cambridge perspective
Towards Responsible Content Mining: A Cambridge perspectiveTowards Responsible Content Mining: A Cambridge perspective
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
 
Disrupting the Publisher-Academic Complex
Disrupting the Publisher-Academic ComplexDisrupting the Publisher-Academic Complex
Disrupting the Publisher-Academic Complexpetermurrayrust
 
Content Mining at Wellcome Trust
Content Mining at Wellcome TrustContent Mining at Wellcome Trust
Content Mining at Wellcome TrustTheContentMine
 
Scientific search for everyone
Scientific search for everyoneScientific search for everyone
Scientific search for everyonepetermurrayrust
 
Rapid biomedical search
Rapid biomedical search Rapid biomedical search
Rapid biomedical search petermurrayrust
 
The culture of researchData
The culture of researchDataThe culture of researchData
The culture of researchDatapetermurrayrust
 
Publishing your research: Open Access (introduction & overview)
Publishing your research: Open Access (introduction & overview)Publishing your research: Open Access (introduction & overview)
Publishing your research: Open Access (introduction & overview)Jamie Bisset
 
Can machines understand the scientific literature
Can machines understand the scientific literatureCan machines understand the scientific literature
Can machines understand the scientific literaturepetermurrayrust
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in Neurosciencepetermurrayrust
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in NeuroscienceTheContentMine
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in NeuroscienceTheContentMine
 
Searching for evidence
Searching for evidenceSearching for evidence
Searching for evidenceAnne Madden
 
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...10 Years Experience in Pioneering Open Access Publishing in Health Informatic...
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...Gunther Eysenbach
 
Early Career Reseachers and Open Healthcare
Early Career Reseachers and Open HealthcareEarly Career Reseachers and Open Healthcare
Early Career Reseachers and Open Healthcarepetermurrayrust
 

Similar to Automated Extraction of Knowledge from Biomedical Literature (20)

ContentMining for France and Europe; Lessons from 2 years in UK
ContentMining for France and Europe; Lessons from 2 years in UKContentMining for France and Europe; Lessons from 2 years in UK
ContentMining for France and Europe; Lessons from 2 years in UK
 
WikiFactMine: Science for Everyone
WikiFactMine: Science for EveryoneWikiFactMine: Science for Everyone
WikiFactMine: Science for Everyone
 
Cohg presentation for drf day
Cohg presentation for drf dayCohg presentation for drf day
Cohg presentation for drf day
 
Why ContentMining is useful
Why ContentMining is usefulWhy ContentMining is useful
Why ContentMining is useful
 
Why ContentMining is useful
Why ContentMining is usefulWhy ContentMining is useful
Why ContentMining is useful
 
Automatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literatureAutomatic Extraction of Science and Medicine from the scholarly literature
Automatic Extraction of Science and Medicine from the scholarly literature
 
Towards Responsible Content Mining: A Cambridge perspective
Towards Responsible Content Mining: A Cambridge perspectiveTowards Responsible Content Mining: A Cambridge perspective
Towards Responsible Content Mining: A Cambridge perspective
 
Disrupting the Publisher-Academic Complex
Disrupting the Publisher-Academic ComplexDisrupting the Publisher-Academic Complex
Disrupting the Publisher-Academic Complex
 
Content Mining at Wellcome Trust
Content Mining at Wellcome TrustContent Mining at Wellcome Trust
Content Mining at Wellcome Trust
 
Scientific search for everyone
Scientific search for everyoneScientific search for everyone
Scientific search for everyone
 
Rapid biomedical search
Rapid biomedical search Rapid biomedical search
Rapid biomedical search
 
The culture of researchData
The culture of researchDataThe culture of researchData
The culture of researchData
 
Publishing your research: Open Access (introduction & overview)
Publishing your research: Open Access (introduction & overview)Publishing your research: Open Access (introduction & overview)
Publishing your research: Open Access (introduction & overview)
 
Can machines understand the scientific literature
Can machines understand the scientific literatureCan machines understand the scientific literature
Can machines understand the scientific literature
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in Neuroscience
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in Neuroscience
 
ContentMining in Neuroscience
ContentMining in NeuroscienceContentMining in Neuroscience
ContentMining in Neuroscience
 
Searching for evidence
Searching for evidenceSearching for evidence
Searching for evidence
 
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...10 Years Experience in Pioneering Open Access Publishing in Health Informatic...
10 Years Experience in Pioneering Open Access Publishing in Health Informatic...
 
Early Career Reseachers and Open Healthcare
Early Career Reseachers and Open HealthcareEarly Career Reseachers and Open Healthcare
Early Career Reseachers and Open Healthcare
 

More from TheContentMine

Open Knowledge and University of Cambridge European Bioinformatics Institute
Open Knowledge and University of Cambridge European Bioinformatics InstituteOpen Knowledge and University of Cambridge European Bioinformatics Institute
Open Knowledge and University of Cambridge European Bioinformatics InstituteTheContentMine
 
ContentMine: Open Data and Social Machines
ContentMine: Open Data and Social MachinesContentMine: Open Data and Social Machines
ContentMine: Open Data and Social MachinesTheContentMine
 
Disruptive Communities and Technology
Disruptive Communities and TechnologyDisruptive Communities and Technology
Disruptive Communities and TechnologyTheContentMine
 
Embrace the Open Revolution
Embrace the Open RevolutionEmbrace the Open Revolution
Embrace the Open RevolutionTheContentMine
 
Content Mining for Machines and Humans
Content Mining for Machines and HumansContent Mining for Machines and Humans
Content Mining for Machines and HumansTheContentMine
 
TheContentMine: Mining for Everyone
TheContentMine: Mining for EveryoneTheContentMine: Mining for Everyone
TheContentMine: Mining for EveryoneTheContentMine
 
Overview of Practical Content Mining
Overview of Practical Content Mining Overview of Practical Content Mining
Overview of Practical Content Mining TheContentMine
 
Copyright Reform and Open Data
Copyright Reform and Open DataCopyright Reform and Open Data
Copyright Reform and Open DataTheContentMine
 
ContentMining and Clinical Trials
ContentMining and Clinical TrialsContentMining and Clinical Trials
ContentMining and Clinical TrialsTheContentMine
 
ContentMine: Liberating scholarship from Open publications and theses
ContentMine: Liberating scholarship from Open publications and thesesContentMine: Liberating scholarship from Open publications and theses
ContentMine: Liberating scholarship from Open publications and thesesTheContentMine
 
ContentMining for Synthetic Biology
ContentMining for Synthetic BiologyContentMining for Synthetic Biology
ContentMining for Synthetic BiologyTheContentMine
 

More from TheContentMine (11)

Open Knowledge and University of Cambridge European Bioinformatics Institute
Open Knowledge and University of Cambridge European Bioinformatics InstituteOpen Knowledge and University of Cambridge European Bioinformatics Institute
Open Knowledge and University of Cambridge European Bioinformatics Institute
 
ContentMine: Open Data and Social Machines
ContentMine: Open Data and Social MachinesContentMine: Open Data and Social Machines
ContentMine: Open Data and Social Machines
 
Disruptive Communities and Technology
Disruptive Communities and TechnologyDisruptive Communities and Technology
Disruptive Communities and Technology
 
Embrace the Open Revolution
Embrace the Open RevolutionEmbrace the Open Revolution
Embrace the Open Revolution
 
Content Mining for Machines and Humans
Content Mining for Machines and HumansContent Mining for Machines and Humans
Content Mining for Machines and Humans
 
TheContentMine: Mining for Everyone
TheContentMine: Mining for EveryoneTheContentMine: Mining for Everyone
TheContentMine: Mining for Everyone
 
Overview of Practical Content Mining
Overview of Practical Content Mining Overview of Practical Content Mining
Overview of Practical Content Mining
 
Copyright Reform and Open Data
Copyright Reform and Open DataCopyright Reform and Open Data
Copyright Reform and Open Data
 
ContentMining and Clinical Trials
ContentMining and Clinical TrialsContentMining and Clinical Trials
ContentMining and Clinical Trials
 
ContentMine: Liberating scholarship from Open publications and theses
ContentMine: Liberating scholarship from Open publications and thesesContentMine: Liberating scholarship from Open publications and theses
ContentMine: Liberating scholarship from Open publications and theses
 
ContentMining for Synthetic Biology
ContentMining for Synthetic BiologyContentMining for Synthetic Biology
ContentMining for Synthetic Biology
 

Recently uploaded

Case Report Peripartum Cardiomyopathy.pptx
Case Report Peripartum Cardiomyopathy.pptxCase Report Peripartum Cardiomyopathy.pptx
Case Report Peripartum Cardiomyopathy.pptxNiranjan Chavan
 
world health day presentation ppt download
world health day presentation ppt downloadworld health day presentation ppt download
world health day presentation ppt downloadAnkitKumar311566
 
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfMedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfSasikiranMarri
 
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners
 
Big Data Analysis Suggests COVID Vaccination Increases Excess Mortality Of ...
Big Data Analysis Suggests COVID  Vaccination Increases Excess Mortality Of  ...Big Data Analysis Suggests COVID  Vaccination Increases Excess Mortality Of  ...
Big Data Analysis Suggests COVID Vaccination Increases Excess Mortality Of ...sdateam0
 
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATROApril 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATROKanhu Charan
 
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfPULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfDolisha Warbi
 
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurMETHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurNavdeep Kaur
 
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranMusic Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranTara Rajendran
 
Radiation Dosimetry Parameters and Isodose Curves.pptx
Radiation Dosimetry Parameters and Isodose Curves.pptxRadiation Dosimetry Parameters and Isodose Curves.pptx
Radiation Dosimetry Parameters and Isodose Curves.pptxDr. Dheeraj Kumar
 
Basic principles involved in the traditional systems of medicine PDF.pdf
Basic principles involved in the traditional systems of medicine PDF.pdfBasic principles involved in the traditional systems of medicine PDF.pdf
Basic principles involved in the traditional systems of medicine PDF.pdfDivya Kanojiya
 
systemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxsystemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxEyobAlemu11
 
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfLippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfSreeja Cherukuru
 
Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Prerana Jadhav
 
Statistical modeling in pharmaceutical research and development.
Statistical modeling in pharmaceutical research and development.Statistical modeling in pharmaceutical research and development.
Statistical modeling in pharmaceutical research and development.ANJALI
 
Culture and Health Disorders Social change.pptx
Culture and Health Disorders Social change.pptxCulture and Health Disorders Social change.pptx
Culture and Health Disorders Social change.pptxDr. Dheeraj Kumar
 
History and Development of Pharmacovigilence.pdf
History and Development of Pharmacovigilence.pdfHistory and Development of Pharmacovigilence.pdf
History and Development of Pharmacovigilence.pdfSasikiranMarri
 
Introduction to Sports Injuries by- Dr. Anjali Rai
Introduction to Sports Injuries by- Dr. Anjali RaiIntroduction to Sports Injuries by- Dr. Anjali Rai
Introduction to Sports Injuries by- Dr. Anjali RaiGoogle
 
Glomerular Filtration and determinants of glomerular filtration .pptx
Glomerular Filtration and  determinants of glomerular filtration .pptxGlomerular Filtration and  determinants of glomerular filtration .pptx
Glomerular Filtration and determinants of glomerular filtration .pptxDr.Nusrat Tariq
 
Apiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptApiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptkedirjemalharun
 

Recently uploaded (20)

Case Report Peripartum Cardiomyopathy.pptx
Case Report Peripartum Cardiomyopathy.pptxCase Report Peripartum Cardiomyopathy.pptx
Case Report Peripartum Cardiomyopathy.pptx
 
world health day presentation ppt download
world health day presentation ppt downloadworld health day presentation ppt download
world health day presentation ppt download
 
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdfMedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
MedDRA-A-Comprehensive-Guide-to-Standardized-Medical-Terminology.pdf
 
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
Wessex Health Partners Wessex Integrated Care, Population Health, Research & ...
 
Big Data Analysis Suggests COVID Vaccination Increases Excess Mortality Of ...
Big Data Analysis Suggests COVID  Vaccination Increases Excess Mortality Of  ...Big Data Analysis Suggests COVID  Vaccination Increases Excess Mortality Of  ...
Big Data Analysis Suggests COVID Vaccination Increases Excess Mortality Of ...
 
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATROApril 2024 ONCOLOGY CARTOON by  DR KANHU CHARAN PATRO
April 2024 ONCOLOGY CARTOON by DR KANHU CHARAN PATRO
 
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdfPULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
PULMONARY EMBOLISM AND ITS MANAGEMENTS.pdf
 
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaurMETHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
METHODS OF ACQUIRING KNOWLEDGE IN NURSING.pptx by navdeep kaur
 
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara RajendranMusic Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
Music Therapy's Impact in Palliative Care| IAPCON2024| Dr. Tara Rajendran
 
Radiation Dosimetry Parameters and Isodose Curves.pptx
Radiation Dosimetry Parameters and Isodose Curves.pptxRadiation Dosimetry Parameters and Isodose Curves.pptx
Radiation Dosimetry Parameters and Isodose Curves.pptx
 
Basic principles involved in the traditional systems of medicine PDF.pdf
Basic principles involved in the traditional systems of medicine PDF.pdfBasic principles involved in the traditional systems of medicine PDF.pdf
Basic principles involved in the traditional systems of medicine PDF.pdf
 
systemic bacteriology (7)............pptx
systemic bacteriology (7)............pptxsystemic bacteriology (7)............pptx
systemic bacteriology (7)............pptx
 
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdfLippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
Lippincott Microcards_ Microbiology Flash Cards-LWW (2015).pdf
 
Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.Presentation on General Anesthetics pdf.
Presentation on General Anesthetics pdf.
 
Statistical modeling in pharmaceutical research and development.
Statistical modeling in pharmaceutical research and development.Statistical modeling in pharmaceutical research and development.
Statistical modeling in pharmaceutical research and development.
 
Culture and Health Disorders Social change.pptx
Culture and Health Disorders Social change.pptxCulture and Health Disorders Social change.pptx
Culture and Health Disorders Social change.pptx
 
History and Development of Pharmacovigilence.pdf
History and Development of Pharmacovigilence.pdfHistory and Development of Pharmacovigilence.pdf
History and Development of Pharmacovigilence.pdf
 
Introduction to Sports Injuries by- Dr. Anjali Rai
Introduction to Sports Injuries by- Dr. Anjali RaiIntroduction to Sports Injuries by- Dr. Anjali Rai
Introduction to Sports Injuries by- Dr. Anjali Rai
 
Glomerular Filtration and determinants of glomerular filtration .pptx
Glomerular Filtration and  determinants of glomerular filtration .pptxGlomerular Filtration and  determinants of glomerular filtration .pptx
Glomerular Filtration and determinants of glomerular filtration .pptx
 
Apiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.pptApiculture Chapter 1. Introduction 2.ppt
Apiculture Chapter 1. Introduction 2.ppt
 

Automated Extraction of Knowledge from Biomedical Literature

  • 1. Cochrane UK & Ireland Symposium 2016, Birmingham, UK, 2016-03-16 Automated Extraction of Knowledge from Biomedical Literature Peter Murray-Rust1,2 [1]University of Cambridge [2]TheContentMine pm286 AT cam DOT ac DOT uk Simple, Universal, Knowledge creation and re-use Our tools and minds are Open. How can we help Cochrane?
  • 2. Overview Content Mining: • Why we need it • What it is • How WE can do it • The next steps • PM-R has worked in Glaxo Group Research on drug discovery, with WHO on adverse events and ICD-10, FDA on NDAs, EPO on patents, etc.
  • 3. The Right to Read is the Right to Mine**PeterMurray-Rust, 2011 http://contentmine.org Not-for-private Profit
  • 4. My European Heroes Young People(ContentMine) NEELIE KROES
  • 5. Output of scholarly publishing [2] https://en.wikipedia.org/wiki/Mont_Blanc#/media/File:Mont_Blanc_depuis_Valmorel.jpg 586,364 Crossref DOIs 201507 [1] per month 1.5 million (papers + supplemental data) /year [citation needed]* each 3 mm thick  4500 m high per year [2] * Most is not Publicly readable [1] http://www.crossref.org/01company/crossref_indicators.html
  • 6. Scientific and Medical publication (STM)[+] • World Citizens pay $450,000,000,000… • … for research in 1,500,000 articles … • … cost $300,000 each to create … • … $7000 each to “publish” [*]… • … $10,000,000,000 from academic libraries … • … to “publishers” who forbid access to 99.9% of citizens of the world … • 85% of medical research is wasted (not published, badly conceived, duplicated, …) [Lancet 2009] [+] Figures probably +- 50 % [*] arXiV preprint server costs $7 USD per paper
  • 7. http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about- ebola.html We were stunned recently when we stumbled across an article by European researchers in Annals of Virology [1982]: “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.” In the future, the authors asserted, “medical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,” referring to hospital-acquired infection. Adage in public health: “The road to inaction is paved with research papers.” Bernice Dahn (chief medical officer of Liberia’s Ministry of Health) Vera Mussah (director of county health services) Cameron Nutt (Ebola response adviser to Partners in Health) A System Failure of Scholarly Publishing
  • 8.
  • 10. WE pay for scholarly publications that WE can’t read [1] The Military-Industrial-Academic complex (1961) (Dwight D Eisenhower, US President) Publishers Academia Glory+? $$, MS review Taxpayer Student Researcher $$ $$ in-kind The Publisher-Academic complex[1]
  • 11. Elsevier wants to control Open Data [asked by Michelle Brook]
  • 12. Prof. Ian Hargreaves (2011): "David Cameron's exam question”: "Could it be true that laws designed more than three centuries ago with the express purpose of creating economic incentives for innovation by protecting creators' rights are today obstructing innovation and economic growth?” “yes. We have found that the UK's intellectual property framework, especially with regard to copyright, is falling behind what is needed.” "Digital Opportunity" by Prof Ian Hargreaves - http://www.ipo.gov.uk/ipreview.htm. Licensed under CC BY 3.0 via Wikipedia - https://en.wikipedia.org/wiki/File:Digital_Opportunity.jpg#/media/File:Digital_Opportunity.jpg
  • 13.
  • 14. Resources • Europe PubMedCentral http://europepmc.org/ • ContentMine toolkit https://github.com/ContentMine/ • Wikidata: https://www.wikidata.org/wiki/Wikidata:Main_Page • Hypothes.is https://hypothes.is/ [1] • Etherpad: http://pads.cottagelabs.com/p/cochrane2016 • Note: early adopters can obtain our (Open) software and run it at home… • [1] Not used in CochraneBham workshop
  • 16.
  • 17. catalogue getpapers query Daily Crawl EPMC, arXiv CORE , HAL, (UNIV repos) ToC services PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJ… Nature, IEEE, Elsevier… Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 30, 000 pages/day Semantic ScholarlyHTML Facts CONTENTMINE Complete OPEN Platform for Mining Scientific Literature dictionaries
  • 19. abstract methods references Captioned Figures Fig. 1 HTML tables abstract methods references Captioned Figures Fig. 1 HTML tables Dict A Dict B Image Caption Table Caption MINING with sections and dictionaries [W3C Annotation / https://hypothes.is/ ]
  • 20. How does Rat find knowledge
  • 21. Demo PMR runs getpapers and ami Chris runs Python visualization of drug co-occurrence
  • 22. I want to see a DEMO Let’s try ChemicalTagger!
  • 24. Open Content Mining of FACTs Machines can interpret chemical reactions We have done 500,000 patents. There are > 3,000,000 reactions/year. Added value > 1B Eur.
  • 25. Dictionaries • Simplest approach to knowledge extraction and management. We’d love to help integrate your dictionaries and Open authorities
  • 26. Disease Dictionary (ICD-10) <dictionary title="disease"> <entry term="1p36 deletion syndrome"/> <entry term="1q21.1 deletion syndrome"/> <entry term="1q21.1 duplication syndrome"/> <entry term="3-methylglutaconic aciduria"/> <entry term="3mc syndrome” <entry term="corpus luteum cyst”/> <entry term="cortical blindness" /> SELECT DISTINCT ?thingLabel WHERE { ?thing wdt:P494 ?wd . ?thing wdt:P279 wd:Q12136 . SERVICE wikibase:label { bd:serviceParam wikibase:language "en" } } wdt:P494 = ICD-10 (P494) identifier wd:Q12136 = disease (Q12136) abnormal condition that affects the body of an organism Wikidata ontology for disease
  • 27. • ChEBI (chemicals at EBI) ftp://ftp.ebi.ac.uk/pub/databases/chebi/Flat_file_tab_delimited/names_3star.tsv.gz) • combined with WIKIDATA: World Health Organisation International Nonproprietary Name (P2275) * => 4947 items in the dictionary (inn.xml) DRUGS <dictionary title="inn"> <entry term="(r)-fenfluramine"/> <entry term="abacavir"/> <entry term="abafungin"/> <entry term="abafungina"/> <entry term="abafungine"/> <entry term="abafunginum"/> <entry term="abamectin"/> <entry term="abarelix"/> <entry term="abatacept"/>
  • 28. <dictionary title="funders"> <!— from http://help.crossref.org/funder-registry with thanks --> <entry id="http://dx.doi.org/10.13039/100001436" term="1675 Foundation"/> <entry id="http://dx.doi.org/10.13039/100004343" term="3M"/> <entry id=“http://dx.doi.org/10.13039/501100005957” term="8020 Promotion Foundation"/> <entry id="http://dx.doi.org/10.13039/501100007139" term="A Richer Life Foundation"/> <entry id="http://dx.doi.org/10.13039/100006543" term="A World Celiac Community Foundation"/> <entry id="http://dx.doi.org/10.13039/100001962" term="A-T Children's Project"/> <entry id="http://dx.doi.org/10.13039/100008456" term="A. Alfred Taubman Medical Research Institute"/> 11566 entries Funders Dictionary
  • 30. <dictionary name="genus"> <entry term="Aa"/> <entry term="Aaaba"/> <entry term="Aacanthocnema"/> <entry term="Aaosphaeria"/> <entry term="Aaptos"/> <entry term="Aaptosyax"/> <entry term="Aaroniella"/> <entry term="Aaronsohnia"/> <entry term="Abablemma"/> Genera from NCBI TaxDump
  • 31. <dictionary title="hgnc"> <entry term="A1BG" name="alpha-1-B glycoprotein"/> <entry term="A1BG-AS1" name="A1BG antisense RNA 1"/> <entry term="A1CF" name="APOBEC1 complementation factor"/> <entry term="A2M" name="alpha-2-macroglobulin"/> <entry term="A2M-AS1" name="A2M antisense RNA 1 (head to head)"/> <entry term="A2ML1" name="alpha-2-macroglobulin-like 1"/> <entry term="A2ML1-AS1" name="A2ML1 antisense RNA 1"/> Human Genes (HGNC)
  • 32. <entry term="Aaas" name="achalasia, adrenocortical insufficiency, alacrimia"/> <entry term="Aacs" name="acetoacetyl-CoA synthetase"/> <entry term="Aadac" name="arylacetamide deacetylase (esterase)"/> <entry term="Aadacl2" name="arylacetamide deacetylase-like 2"/> <entry term="Aadacl3" name="arylacetamide deacetylase-like 3"/> <entry term="Aadat" name="aminoadipate aminotransferase"/> <entry term="Aaed1" name="AhpC/TSA antioxidant enzyme domain containing 1"/> <entry term="Aagab" name="alpha- and gamma-adaptin binding protein"/> <entry term="Aak1" name="AP2 associated kinase 1"/> <entry term="Aamdc" name="adipogenesis associated Mth938 domain containing"/> <entry term="Aamp" name="angio-associated migratory protein"/> Mouse genes (JAXson)
  • 34. <dictionary title="tropicalVirus"> <entry term="ZIKV" name="Zika virus"/> <entry term="Zika" name="Zika virus"/> <entry term="DENV" name="Dengue virus"/> <entry term="Dengue" name="Dengue virus"/> <entry term="CHIKV" name="Chikungunya virus"/> <entry term="Chikungunya" name="Chikungunya virus"/> <entry term="WNV" name="West Nile virus"/> <entry term="West Nile" name="West Nile virus"/> <entry term="YFV" name="Yellow fever virus"/> <entry term="Yellow fever" name="Yellow fever virus"/> <entry term="HPV" name="Human papilloma virus"/> <entry term="Human papilloma virus" name="Human papilloma virus"/> </dictionary> Terms co-ocurring with “Zika”
  • 35. <dictionary title="cochrane"> <entry term="Cochrane Library"/> <entry term="Cochrane Reviews"/> <entry term="Cochrane Central Register of Controlled Trials"/> <entry term="Cochrane"/> <entry term="randomize"/> <entry term="meta-analysis"/> <entry term="Embase"/> <entry term="MEDLINE"/> <entry term="eligibility"/> <entry term="exclusion"/> <entry term="outcome"/> <entry term="Review Manager"/> <entry term="STATA"/> <entry term="RCT"/> </dictionary> Terms lexically related to “meta-analysis”
  • 36. Mining strategy • Discover. negotiate permissions . => bibliography • Crawl / Scrape (download), documents AND supplemental • Normalize. PDF => XML • Index: facets => Facts and snippets (“entities”) • Interpret/analyze entities => relationships, aggregations (“Transformative”) • Publish
  • 37. catalogue getpapers query Daily Crawl EuPMC, arXiv CORE , HAL, (UNIV repos) ToC services PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJ… Nature, IEEE, Elsevier… Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 30, 000 pages/day Semantic ScholarlyHTML Facts CONTENTMINE Complete OPEN Platform for Mining Scientific Literature
  • 39. Systematic Reviews Can we: • eliminate true negatives automatically? • extract data from formulaic language? • mine diagrams? • Annotate existing sources? • forward-reference clinical trials?
  • 40. Polly has 20 seconds to read this paper… …and 10,000 more
  • 41. ContentMine software can do this in a few minutes Polly: “there were 10,000 abstracts and due to time pressures, we split this between 6 researchers. It took about 2-3 days of work (working only on this) to get through ~1,600 papers each. So, at a minimum this equates to 12 days of full-time work (and would normally be done over several weeks under normal time pressures).”
  • 42. 400,000 Clinical Trials In 10 government registries Mapping trials => papers http://www.trialsjournal.com/content/16/1/80 2009 => 2015. What’s happened in last 6 years?? Search the whole scientific literature For “2009-0100068-41”
  • 47. But we can now turn PDFs into Science We can’t turn a hamburger into a cow Pixel => Path => Shape => Char => Word => Para => Document => SCIENCE
  • 51. Ln Bacterial load per fly 11.5 11.0 10.5 10.0 9.5 9.0 6.5 6.0 Days post—infection 0 1 2 3 4 5 Bitmap Image and Tesseract OCR
  • 52.
  • 53.
  • 57. @Senficon (Julia Reda) :Text & Data mining in times of #copyright maximalism: "Elsevier stopped me doing my research" http://onsnetwork.org/chartgerink/2015/11/16/elsevi er-stopped-me-doing-my-research/ … #opencon #TDM Elsevier stopped me doing my research Chris Hartgerink
  • 58. I am a statistician interested in detecting potentially problematic research such as data fabrication, which results in unreliable findings and can harm policy-making, confound funding decisions, and hampers research progress. To this end, I am content mining results reported in the psychology literature. Content mining the literature is a valuable avenue of investigating research questions with innovative methods. For example, our research group has written an automated program to mine research papers for errors in the reported results and found that 1/8 papers (of 30,000) contains at least one result that could directly influence the substantive conclusion [1]. In new research, I am trying to extract test results, figures, tables, and other information reported in papers throughout the majority of the psychology literature. As such, I need the research papers published in psychology that I can mine for these data. To this end, I started ‘bulk’ downloading research papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention to redistribute the downloaded materials, had legal access to them because my university pays a subscription, and I only wanted to extract facts from these papers. Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days. This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day. Approximately two weeks after I started downloading psychology research papers, Elsevier notified my university that this was a violation of the access contract, that this could be considered stealing of content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading (which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university. I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly hampering me in my research. [1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods, 1–22. doi: 10.3758/s13428-015-0664-2 Chris Hartgerink’s blog post
  • 59. WILEY … “new security feature… to prevent systematic download of content “[limit of] 100 papers per day” “essential security feature … to protect both parties (sic)” CAPTCHA User has to type words
  • 60. http://onsnetwork.org/chartgerink/2016/02/23/wiley-also-stopped-my-doing-my-research/ Wiley also stopped me (Chris Hartgerink) doing my research In November, I wrote about how Elsevier wanted me to stop downloading scientific articles for my research. Today, Wiley also ordered me to stop downloading. As a quick recapitulation: I am a statistician doing research into detecting potentially problematic research such as data fabrication and estimating how often it occurs. For this, I need to download many scientific articles, because my research applies content mining methods that extract facts from them (e.g., test statistics). These facts serve as my data to answer my research questions. If I cannot download these research articles, I cannot collect the data I need to do my research. I was downloading psychology research articles from the Wiley library, with a maximum of 5 per minute. I did this using the tool quickscrape, developed by the ContentMine organization. With this, I have downloaded approximately 18,680 research articles from the Wiley library, which I was downloading solely for research purposes. Wiley noticed my downloading and notified my university library that they detected a compromised proxy, which they had immediately restricted. They called it “illegally downloading copyrighted content licensed by your institution”. However, at no point was there any investigation into whether my user credentials were actually compromised (they were not). Whether I had legitimate reasons to download these articles was never discussed. The original email from Wiley is available here. As a result of Wiley denying me to download these research articles, I cannot collect data from another one of the big publishers, alongside Elsevier. Wiley is more strict than Elsevier by immediately condemning the downloading as illegal, whereas Elsevier offers an (inadequate) API with additional terms of use (while legitimate access has already been obtained). I am really confused about what the publisher’s stance on content mining is, because Sage and Springer seemingly allow it; I have downloaded 150,210 research articles from Springer and 12,971 from Sage and they never complained about it.
  • 61.
  • 62. ContentMine can Offer • Collaboration • Prototyping. YOU design the rules and system • Rapid knowledge creation and analysis tools accessible to EVERYONE and controlled by ANYONE. • Access to ALL daily scientific/medical FACTs ContentMine needs • Joint projects with narratives • Support in kind (code, content) and cash. • http://contentmine.org
  • 63. ContentMine can Offer • Collaboration • Prototyping • Rapid knowledge creation and analysis tools accessible to EVERYONE and controlled by ANYONE. • Access to ALL daily scientific/medical FACTs ContentMine needs • Joint projects with narratives • Support in kind (code, content) and cash. • http://contentmine.org KNOWLEDGE SAVES LIVES