APPILCATIONS OF AI AND ML IN REAL LIFE

1. APPLICATION OF AI IN
HEALTCARE

2. INTRODUCTION
 Healthcare has always involved the intersection of human judgement
and scientific data. Advancements in artificial intelligence (AI) are
bringing those two elements closer than ever—and the industry is
feeling the impact.
 Defined as “computer systems able to perform tasks that usually
require human intelligence,” data-based artificial intelligence analyzes
large amounts of data using algorithms to learn how to do tasks
without being explicitly programmed. That capability is creating
waves of change as AI in healthcare proves to be a critical component
in diagnosis, treatment, care delivery, outcomes and cost.
 From big data to policy, artificial intelligence is significantly changing
the healthcare industry.

3. CLINICAL DECISION SUPPORT
 Across the healthcare industry, artificial intelligence is changing the
way clinical providers make decisions. More than ever, it’s playing a
key role in clinical decision support as it delivers data to providers to
aid in diagnosing, treatment planning and population health
management.
 Consider all the vast amounts of data that AI has the potential to
harness—from genomic, biomarker and phenotype data to health
records and delivery systems. The technology is already being used to
support decisions made in data-intensive specialties like radiology,
pathology and ophthalmology. In the future, it may even be possible
to perform certain tasks autonomously using this technology.

4. The key to safe and effective integration of AI in healthcare is rigorous and ongoing evaluation. Systems
will continue to improve as AI-enabled decision-making is applied practically, in hospitals and doctor’s
offices around the world.
Artificial intelligence even has the potential to decrease the administrative burden on clinicians by
improving clinical decision software. With natural language processing, the technology can help translate
clinical notes in EHRs. That means a clinician only needs to enter data once. AI-enabled software can also
provide access to data from multiple sources—including medical images, EHR data and even consumer
devices such as activity trackers, smartphones and connected medical devices. This expands the
diagnostic and treatment options clinicians can propose—and has the power to transform health
outcomes and create more personalized care delivery.

5. COST
 As the industry shifts, there is great opportunity to use AI in healthcare to
help drive cost savings.
 Leonard D’Avolio, PhD, founder and CEO of Cyft—a company helping
organizations use technology to adjust their workflow and systems to
reduce cost and improve outcomes—sees artificial intelligence not as a
solution but as a capability, allowing us to learn from data in ways we
never could before. And that takes an investment. During a HIMSS TV
interview, Dr. D’Avolio acknowledged that change is hard in healthcare,
but that change is also a prerequisite for improvement.
 His advice for those beginning AI implementation projects: “You need
executive level sponsorship, and you need to pick a problem with a really
solid five-to-one return on investment. Fall in love with the problem, not
necessarily the solution.” He encourages healthcare organizations to form
a working group with data scientists working arm-in-arm with project
managers and the IT team to effectively implement the technology. And
then measure the impact.

6. “You don’t want to wait a year and then look at admission rates or total medical expense. You need
to measure baseline, activities, outcomes, every step of the way. If you want people to get behind
AI, you need to be able to show them it’s worth it.”
Jonathan Bush, executive chairman of Firefly Health, sees artificial intelligence as a way to clean up
the estimated $91 billion in wasted healthcare spending that comes from inefficient administration.
“Most healthcare executives are still unsure of their AI strategy. They sense that AI will be a game
changer, but they’re not sure how. I love that healthcare has heroic ambitions for a promising new
technology, even after years of high-tech disappointment. But while we shoot for the moon, let’s
clean up the muck that’s bogging us down today, unleashing our potential to transform healthcare.”

7. PATIENT DATA
 As the technology is integrated into healthcare, it will become easier to find meaning in
the massive mountains of patient data. Lily Peng, MD, PhD, product manager in the
Google Brain AI Research Group, explained that while human intelligence is best suited
for integrating small numbers of very large effect factors, AI is particularly adept
at combing through and identifying patterns in vast numbers and obscure factors.
 Chris DeRienzo, MD, MPP, FAAP, senior vice president, chief quality and medical staff
officer, WakeMed Health and Hospitals, sees the potential for artificial intelligence to
“bend the laws of physics” by allowing one experienced doctor to treat many more
patients. “We live in an era of augmented intelligence, where our smartphones use
algorithms to guess where we want to go or what we want to say next. The key benefits
of artificial intelligence are grounded in this ability to continuously comb the EMR,
training on past patients’ trajectories in the same way clinicians are trained and hone
the lenses of their own prescription glasses, patient by patient by the millions.”

8. Mark Weber, senior vice president, Infor Health Solutions, also sees the potential in applying
machine learning and AI in healthcare similar to how it’s applied to consumer marketing. “For
example, if I buy hiking boots online, suggested items pop up that I can use as well, like bug spray
or sunscreen. The data analytics behind those recommendations includes a wealth of information
about me—my demographics, such as age, gender, education and income level, as well as where I
live and other factors that influence my buying decisions. My prediction is that we will be able to
apply the same principles to healthcare data—to improve patient outcomes, costs and efficiencies.”

9. PRECISION MEDICINE
 Precision medicine, per the U.S. National Institutes of Health, is “an emerging approach for
disease treatment and prevention that takes into account individual variability in genes,
environment, and lifestyle for each person.” Artificial intelligence algorithms can
take precision medicine to the next level by increasing the accuracy and prediction of
outcomes through mining large quantities of genetic, clinical, social, lifestyle and
preference data across broad, heterogenous populations, shared Dixie B. Baker, PhD,
FHIMSS, senior partner, Martin, Blanck and Associates.
 A report from Chilmark Research goes so far as to state that precision medicine must be
accompanied by machine learning and artificial intelligence to reap its full rewards—due to
the ability to analyze large data sets faster than clinicians and medical researchers.
 AI delivers major benefits to advancing precision medicine, not only in predicting
outcomes of current patients, but even in predicting the probability of future patients’
having a disease. With this level of insight, providers can know the best care plan not only
for individuals, but for entire populations.

10. SECURITY
 The healthcare industry must be vigilant in securing and protecting
technologies with vulnerabilities that can be exploited like artificial
intelligence and machine learning. “AI is a dual-use technology that can
be deployed defensively or offensively,” said Lee Kim, JD, CISSP, CIPP/US,
FHIMSS, director of privacy and security at HIMSS. “The malicious use of
AI will impact how we construct and manage our digital infrastructure as
well as how we design and distribute AI systems, and will likely require
policy and other institutional responses.”
 In the cybersecurity realm, AI in healthcare can be used to automate
phishing, the initial point of compromise in most cyberattacks. Spear-
phishing, often tailored to the recipient using intelligence gathered about
the recipient is even more damaging, with fully automated attacks
potentially disruptive for many organizations. Artificial intelligence
systems may also be used for other nefarious purposes, such as
automated cyber-attacks on hospital networks, potentially putting lives at
risk—especially those patients that depend upon life-saving or life-
sustaining devices that have network connectivity.

11. CONCLUSION
 Clearly, AI in healthcare is changing the industry across the spectrum. But
as humans, we don’t just want to know how. We want to know why—
because we are capable of asking the big questions and looking at the
ramifications of technology and infrastructure.
 Dr. DeRienzo said it well:
 “Our central purpose in designing, developing and deploying artificial-
intelligence-based patient care technology solutions must be grounded in
helping clinicians return to their patients’ bedsides, be they at home or in
hospital, and serve them with more connected information, more
upstream interventions and more time to spend with the patients who
most need their human bond… Once our purpose is clear, we must
incorporate human factors from the outset of design, and continually ask
and answer the question, throughout development, how will this tool
help humans better serve other humans?”