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HEALTH INFORMATICS
Digital Health Trends (2022)
Presented by: Ronel Wynlor D. Abarca, RMT
Digital Health
• First introduced by Frank in 2000 in a
journal article entitled Digital Health
Care—The Convergence of Health
Care and the Internet
Medical Care &
World Wide Web
(Frank, 2000)
Internet of Medical
Things from the
concept Internet of
Things introduced by
Kevin Ashton in 2000
eHealth & mHealth
(WHO, 2019
Use of Artificial
Intelligence
(Chang, 2020)
Digital
Health
• Digital Health is COVID-19 Pandemic’s
Legacy (Bruining, 2021).
• According to Matthews et al. (2019),
investments in Digital Health
skyrocketed to 6 billion US dollars by
the year 2017.
Digital Health & Internet
Ease of Communication using IoT in Health
• Remote Diagnosis in Emergency Scenarios through body sensor networks and wearable
sensors (Ratta et al., 2021)
• Improved overall performance of healthcare system during pandemic by allowing
connectivity of physical objects through the internet (Javaiad & Khan, 2021)
Dominant in Literature Search using
Google Scholar with the keyword Medical
Internet of Things
• Analyze athletes’ conditions and offer proper medications even if doctors are away using
Smart Healthcare Monitoring Systems (Wu et. al, 2021)
• Telemedicine allows remote communication between doctors and patients and is preferred
by most patients due to current state of COVID-19 as it reduces exposure in hospitals and
medical centers (Anthony Jnr, 2021)
Digital Health Trends (TMF, 2022)
Patient Empowerment
Lifestyle Medicine
Globalized Healthcare
Pharma companies & Digital Health
Direct-to-consumer Genetic Testing
Nutrigenomics
Food Scanners
Portable Diagnostic Devices
A.I Guided Ultrasound
Conscious Health Consumer
Virtual Visits and Chatbots
Artificial Intelligence
Bioprinting
3D Printing
Automation
COVID-19
Mixed Reality
Virtual Reality
Robots
Digital Health Insurance
Digital Health Trends (TMF, 2022)
The top 20 trends can be condensed into the following themes:
• Telemedicine
a. Virtual Visits and Chatbots
b. Virtual Reality
c. Pharmacy Digital Health Service
• Artificial Intelligence
a. Virtual Visits and Chatbots
b. Robots
c. Virtual Reality
d. Mixed Reality
e. Automation
f. Bioprinting & 3D Printing
g. Portable Diagnostic Devices
• Patient-Oriented Care & Precision Medicine
a. Lifestyle Medicine
b. Globalized Health Care
c. Patient Empowerment
d. Nutrigenomics
e. Food Scanners
f. Direct-to-consumer Genetic Testing
• COVID-19
• Catalyst of Digital Health
Digital Health & COVID-19
Ø From The Lancet, 11 out of the 55 results related to Digital Health made
actual mention of COVID-19 and direct link to Digital Health.
ü Bengio et al. (2020) Privacy in Public Digital Contact Tracing for COVID-19
ü Braithwaite et al. (2020) Automated and Partly automated contact tracing
ü Cosgriff et al. (2020) Data Sharing in COVID-19 era
ü Gasser et al. (2020) Ethical Challenges on COVID-19 Digital Tools
ü Gunasekeran et al. (2021) Digital Health in Ophthalmology during COVID-19
ü McCall (2020) COVID-19 and Artificial Intelligence
ü Schwamm et al. (2020) COVID-19 catalyzed Virtual Model of Care
ü Tsao et al. (2021) Social Media and COVID-19
ü Watts (2020) COVID-19 and Digital Divide
ü Whitelaw et al. (2020) Digital Technology in COVID-19 Planning & Response
ü Zhoue et al. (2020) Artificial Intelligence for COVID-19 Drug repurposing
Using Google Scholar and the
keyword “Digital Health” alone,
COVID-19 is inevitably linked to it
in literatures published since 2020.
Using the Metrics function of
Google Scholar, the predominance
of COVID-19 in Digital Health
publications was investigated.
The Lancet was selected being the
top publication with 55 results
related to Digital Health.
Google Scholar Metrics uses h5-
index thereby it look for literatures
published in the past 5 years.
Digital Health & COVID-19
• Primary Trends regarding COVID-19 & Digital health
Ø Pandemic Response using Digital Health as mentioned by
Whitelaw et al. (2020)
§ According to Tilahun et al. (2021) the lessons brought by
the COVID-19 pandemic should be applied to future
digital health technologies to refine health system
response for future pandemics.
Ø Digital Contact Tracing as mentioned by Braithwaite et al.
(2020)
§ Manual Contact Tracing à Intensive, Time-consuming,
Delays (Keeling et al., 2020)
§ Digital Contact Tracing à address the limitations of
Manual Tracing (Ferretti et al., 2020)
ü Automation à Results and symptom reports
ü Utilizing smartphone capabilities such as Bluetooth
Digital Health & COVID-19
• Primary Trends regarding COVID-19 &
Digital health
Ø Improving Data Privacy measures and
Addressing Ethical Issues
§ According to Gasser et al. (2020), violation
to patient Autonomy is the most obvious
ethical drawback of digital health
technology.
ü Mandatory use of apps
ü Apps that include permissions to
collect data beyond their stated
purpose.
§ Loftus et al. (2022) proposed the usage of an
algorithm that will ensure ethical usage of
digital technologies in health using 6 desirable
characteristics.
Digital Health & COVID-19
• The Rise of Telemedicine
Ø Telemedicine has taken the center stage when the
COVID-19 held its grip on the whole world (Marin,
2020).
Ø The pandemic acted as a catalyst in making digital
solutions and advanced technology tools in healthcare
adopted in a global scale (Omboni et al., 2022).
Ø During the height of the pandemic, it permitted
patients with mild disease to get the care they need
while minimizing their exposure to other people
(Portnoy et al., 2020).
Digital Health & COVID-19
• Future of Telemedicine
v Areas to Improve according to Omboni et al. (2022)
1. Policies to legislate telemedicine, license
healthcare operators, protect patients’ privacy,
and implement reimbursement plans
2. Guidelines for the routine clinical use of
telemedicine in different contexts;
3. Integration of telemedicine with traditional
healthcare services
4. Awareness of and willingness to use telemedicine
5. Technological, infrastructural, and economic
barriers.
Digital Health & AI
ARTIFICIAL
INTELLIGENCE
Wearable Devices
AI-Powered Digital
Health Platforms
Bioprinting & 3D
Printing
Wearable ECG
Improved health outcomes for seniors in assisted
living communities (Wilmink et al., 2020)
Weight Reduction associated with preventive
programs via digital health platform
(Auster-Gussman et al., 2022)
Patch via Bluetooth (Lin et al., 2019)
Watch (Randazzo et al., 2019)
Bioprinting of Kidney
(Fransen et al., 2021)
Chatbots
Ask Rosa – Breast & Ovarian Cancer Chatbot
(Siglen et al., 2022)
HealthBots in Telemedicine
(Vasileiou & Maglogiannis, 2022)
Bioprinting of Blood Vessels
(Wang et al., 2022)
Digital Health & AI
Healthcare Robots
https://www.aldebaran.com/en/blog/news-trends/how-have-
humanoid-robots-been-effective-supporting-our-healthcare-
workers-during
https://www.medicaldevice-network.com/comment/what-are-
the-main-types-of-robots-used-in-healthcare/
v Robots reduces Workload and Enhances
Healthcare Experience (Kaiser et al., 2021)
v Multitasking-Intelligent Nurse Aid (MINA)
Robot to reduce nurse burnout
(Nambiappan et al., 2021)
v CHARMIE Assistant Robot for Elderly Care
(Ribeiro et al., 2021)
Digital Health Trends
deloitte.com/us/en/insights/industry/health-care/digital-health-trends.html telepaxx.com/study-reveals-digital-healthcare-market-grows-faster-than-expected/
References
Anthony Jnr, B. (2021). Integrating telemedicine to support digital health care for the management of COVID-19 pandemic.
https://doi.org/10.1080/20479700.2020.1870354
Auster-Gussman, L. A., Lockwood, K. G., Graham, S. A., Pitter, V., & Branch, O. L. H. (2022). Engagement in Digital Health App-Based Prevention Programs Is Associated
With Weight Loss Among Adults Age 65+. Frontiers in Digital Health, 4, 886783. https://doi.org/10.3389/FDGTH.2022.886783
Bengio, Y., Janda, R., Yu, Y. W., Ippolito, D., Jarvie, M., Pilat, D., Struck, B., Krastev, S., & Sharma, A. (2020). The need for privacy with public digital contact tracing
during the COVID-19 pandemic. The Lancet Digital Health, 2(7), e342–e344. https://doi.org/10.1016/S2589-7500(20)30133-3
Braithwaite, I., Callender, T., Bullock, M., & Aldridge, R. W. (2020). Automated and partly automated contact tracing: a systematic review to inform the control of COVID-
19. The Lancet Digital Health, 2(11), e607–e621. https://doi.org/10.1016/S2589-7500(20)30184-9
Bruining, N. (2021). The post-pandemic legacy: the breakthrough of digital health and telemedicine. Cardiovascular Research, 117(9), e118–e119.
https://doi.org/10.1093/CVR/CVAB178
Chang, A. (2020). The Role of Artificial Intelligence in Digital Health. 71–81. https://doi.org/10.1007/978-3-030-12719-0_7
Cosgriff, C. v., Ebner, D. K., & Celi, L. A. (2020). Data sharing in the era of COVID-19. The Lancet Digital Health, 2(5), e224.
https://doi.org/10.1016/S2589-7500(20)30082-0
References
Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dörner, L., Parker, M., Bonsall, D., & Fraser, C. (2020). Quantifying SARS-CoV-2 transmission suggests
epidemic control with digital contact tracing. Science (New York, N.Y.), 368(6491). https://doi.org/10.1126/SCIENCE.ABB6936
Frank, S. R. (2000). Digital Health Care—The Convergence of Health Care and the Internet. The Journal of Ambulatory Care Management, 23(2).
https://journals.lww.com/ambulatorycaremanagement/Fulltext/2000/04000/Digital_Health_Care_The_Convergence_of_Health_Care.3.aspx
Fransen, M. F. J., Addario, G., Bouten, C. V. C., Halary, F., Moroni, L., & Mota, C. (2021). Bioprinting of kidney in vitro models: cells, biomaterials, and manufacturing
techniques. Essays in Biochemistry, 65(3), 587–602. https://doi.org/10.1042/EBC20200158
Gasser, U., Ienca, M., Scheibner, J., Sleigh, J., & Vayena, E. (2020). Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid. The Lancet Digital
Health, 2(8), e425–e434. https://doi.org/10.1016/S2589-7500(20)30137-0
Gunasekeran, D. v., Tham, Y. C., Ting, D. S. W., Tan, G. S. W., & Wong, T. Y. (2021). Digital health during COVID-19: lessons from operationalising new models of care in
ophthalmology. The Lancet Digital Health, 3(2), e124–e134. https://doi.org/10.1016/S2589-7500(20)30287-9
Javaid, M., & Khan, I. H. (2021). Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic. Journal of Oral Biology and
Craniofacial Research, 11(2), 209–214. https://doi.org/10.1016/J.JOBCR.2021.01.015
References
Kaiser, M. S., al Mamun, S., Mahmud, M., & Tania, M. H. (2021). Healthcare Robots to Combat COVID-19. Lecture Notes on Data Engineering and Communications
Technologies, 60, 83–97. https://doi.org/10.1007/978-981-15-9682-7_10/COVER
Keeling, M. J., Hollingsworth, T. D., & Read, J. M. (2020). Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19). Journal of
Epidemiology and Community Health, 74(10), 861. https://doi.org/10.1136/JECH-2020-214051
Lin, Y. J., Chuang, C. W., Yen, C. Y., Huang, S. H., Huang, P. W., Chen, J. Y., & Lee, S. Y. (2019). Artificial Intelligence of Things Wearable System for Cardiac Disease
Detection. Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, 67–70.
https://doi.org/10.1109/AICAS.2019.8771630
Loftus ID, T. J., Tighe ID, P. J., Ozrazgat-Baslanti, T. I., Davis, J. P., RuppertID, M. M., RenID, Y., ShickelID, B., KamaleswaranID, R., HoganID, W. R., Randall Moorman, J.,
Upchurch, G. R., Rashidi, P., & BihoracID, A. (2022). Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible. PLOS Digital
Health, 1(1), e0000006. https://doi.org/10.1371/JOURNAL.PDIG.0000006
Marin, A. (2020). Technology Feature | Telemedicine takes center stage in the era of COVID-19. Science, 370(6517), 731–733.
https://doi.org/10.1126/SCIENCE.370.6517.731
Mathews, S. C., McShea, M. J., Hanley, C. L., Ravitz, A., Labrique, A. B., & Cohen, A. B. (2019). Digital health: a path to validation. Npj Digital Medicine 2019 2:1, 2(1),
1–9. https://doi.org/10.1038/s41746-019-0111-3
References
McCall, B. (2020). COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread. The Lancet Digital Health, 2(4), e166–e167.
https://doi.org/10.1016/s2589-7500(20)30054-6
Nambiappan, H. R., Kodur, K. C., Kyrarini, M., Makedon, F., & Gans, N. (2021). MINA: A Multitasking Intelligent Nurse Aid Robot. ACM International Conference
Proceeding Series, 266–267. https://doi.org/10.1145/3453892.3461010
Omboni, S., Padwal, R. S., Alessa, T., Benczúr, B., Green, B. B., Hubbard, I., Kario, K., Khan, N. A., Konradi, A., Logan, A. G., Lu, Y., Mars, M., McManus, R. J., Melville, S.,
Neumann, C. L., Parati, G., Renna, N. F., Ryvlin, P., Saner, H., … Wang, J. (2022). The worldwide impact of telemedicine during COVID-19: current evidence and r
ecommendations for the future. Connected Health, 1, 7. https://doi.org/10.20517/CH.2021.03
Portnoy, J., Waller, M., & Elliott, T. (2020). Telemedicine in the Era of COVID-19. Journal of Allergy and Clinical Immunology: In Practice, 8(5), 1489–1491.
https://doi.org/10.1016/j.jaip.2020.03.008
Randazzo, V., Ferretti, J., & Pasero, E. (2019). ECG WATCH: A real time wireless wearable ECG. Medical Measurements and Applications, MeMeA 2019 - Symposium
Proceedings. https://doi.org/10.1109/MEMEA.2019.8802210
Ratta, P., Kaur, A., Sharma, S., Shabaz, M., & Dhiman, G. (2021). Application of Blockchain and Internet of Things in Healthcare and Medical Sector: Applications,
Challenges, and Future Perspectives. Journal of Food Quality, 2021. https://doi.org/10.1155/2021/7608296
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Ribeiro, T., Gonçalves, F., Garcia, I. S., Lopes, G., & Ribeiro, A. F. (2021). CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care.
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DIGITAL HEALTH TRENDS.pdf

  • 1. HEALTH INFORMATICS Digital Health Trends (2022) Presented by: Ronel Wynlor D. Abarca, RMT
  • 2. Digital Health • First introduced by Frank in 2000 in a journal article entitled Digital Health Care—The Convergence of Health Care and the Internet Medical Care & World Wide Web (Frank, 2000) Internet of Medical Things from the concept Internet of Things introduced by Kevin Ashton in 2000 eHealth & mHealth (WHO, 2019 Use of Artificial Intelligence (Chang, 2020) Digital Health • Digital Health is COVID-19 Pandemic’s Legacy (Bruining, 2021). • According to Matthews et al. (2019), investments in Digital Health skyrocketed to 6 billion US dollars by the year 2017.
  • 3. Digital Health & Internet Ease of Communication using IoT in Health • Remote Diagnosis in Emergency Scenarios through body sensor networks and wearable sensors (Ratta et al., 2021) • Improved overall performance of healthcare system during pandemic by allowing connectivity of physical objects through the internet (Javaiad & Khan, 2021) Dominant in Literature Search using Google Scholar with the keyword Medical Internet of Things • Analyze athletes’ conditions and offer proper medications even if doctors are away using Smart Healthcare Monitoring Systems (Wu et. al, 2021) • Telemedicine allows remote communication between doctors and patients and is preferred by most patients due to current state of COVID-19 as it reduces exposure in hospitals and medical centers (Anthony Jnr, 2021)
  • 4. Digital Health Trends (TMF, 2022) Patient Empowerment Lifestyle Medicine Globalized Healthcare Pharma companies & Digital Health Direct-to-consumer Genetic Testing Nutrigenomics Food Scanners Portable Diagnostic Devices A.I Guided Ultrasound Conscious Health Consumer Virtual Visits and Chatbots Artificial Intelligence Bioprinting 3D Printing Automation COVID-19 Mixed Reality Virtual Reality Robots Digital Health Insurance
  • 5. Digital Health Trends (TMF, 2022) The top 20 trends can be condensed into the following themes: • Telemedicine a. Virtual Visits and Chatbots b. Virtual Reality c. Pharmacy Digital Health Service • Artificial Intelligence a. Virtual Visits and Chatbots b. Robots c. Virtual Reality d. Mixed Reality e. Automation f. Bioprinting & 3D Printing g. Portable Diagnostic Devices • Patient-Oriented Care & Precision Medicine a. Lifestyle Medicine b. Globalized Health Care c. Patient Empowerment d. Nutrigenomics e. Food Scanners f. Direct-to-consumer Genetic Testing • COVID-19 • Catalyst of Digital Health
  • 6. Digital Health & COVID-19 Ø From The Lancet, 11 out of the 55 results related to Digital Health made actual mention of COVID-19 and direct link to Digital Health. ü Bengio et al. (2020) Privacy in Public Digital Contact Tracing for COVID-19 ü Braithwaite et al. (2020) Automated and Partly automated contact tracing ü Cosgriff et al. (2020) Data Sharing in COVID-19 era ü Gasser et al. (2020) Ethical Challenges on COVID-19 Digital Tools ü Gunasekeran et al. (2021) Digital Health in Ophthalmology during COVID-19 ü McCall (2020) COVID-19 and Artificial Intelligence ü Schwamm et al. (2020) COVID-19 catalyzed Virtual Model of Care ü Tsao et al. (2021) Social Media and COVID-19 ü Watts (2020) COVID-19 and Digital Divide ü Whitelaw et al. (2020) Digital Technology in COVID-19 Planning & Response ü Zhoue et al. (2020) Artificial Intelligence for COVID-19 Drug repurposing Using Google Scholar and the keyword “Digital Health” alone, COVID-19 is inevitably linked to it in literatures published since 2020. Using the Metrics function of Google Scholar, the predominance of COVID-19 in Digital Health publications was investigated. The Lancet was selected being the top publication with 55 results related to Digital Health. Google Scholar Metrics uses h5- index thereby it look for literatures published in the past 5 years.
  • 7. Digital Health & COVID-19 • Primary Trends regarding COVID-19 & Digital health Ø Pandemic Response using Digital Health as mentioned by Whitelaw et al. (2020) § According to Tilahun et al. (2021) the lessons brought by the COVID-19 pandemic should be applied to future digital health technologies to refine health system response for future pandemics. Ø Digital Contact Tracing as mentioned by Braithwaite et al. (2020) § Manual Contact Tracing à Intensive, Time-consuming, Delays (Keeling et al., 2020) § Digital Contact Tracing à address the limitations of Manual Tracing (Ferretti et al., 2020) ü Automation à Results and symptom reports ü Utilizing smartphone capabilities such as Bluetooth
  • 8. Digital Health & COVID-19 • Primary Trends regarding COVID-19 & Digital health Ø Improving Data Privacy measures and Addressing Ethical Issues § According to Gasser et al. (2020), violation to patient Autonomy is the most obvious ethical drawback of digital health technology. ü Mandatory use of apps ü Apps that include permissions to collect data beyond their stated purpose. § Loftus et al. (2022) proposed the usage of an algorithm that will ensure ethical usage of digital technologies in health using 6 desirable characteristics.
  • 9. Digital Health & COVID-19 • The Rise of Telemedicine Ø Telemedicine has taken the center stage when the COVID-19 held its grip on the whole world (Marin, 2020). Ø The pandemic acted as a catalyst in making digital solutions and advanced technology tools in healthcare adopted in a global scale (Omboni et al., 2022). Ø During the height of the pandemic, it permitted patients with mild disease to get the care they need while minimizing their exposure to other people (Portnoy et al., 2020).
  • 10. Digital Health & COVID-19 • Future of Telemedicine v Areas to Improve according to Omboni et al. (2022) 1. Policies to legislate telemedicine, license healthcare operators, protect patients’ privacy, and implement reimbursement plans 2. Guidelines for the routine clinical use of telemedicine in different contexts; 3. Integration of telemedicine with traditional healthcare services 4. Awareness of and willingness to use telemedicine 5. Technological, infrastructural, and economic barriers.
  • 11. Digital Health & AI ARTIFICIAL INTELLIGENCE Wearable Devices AI-Powered Digital Health Platforms Bioprinting & 3D Printing Wearable ECG Improved health outcomes for seniors in assisted living communities (Wilmink et al., 2020) Weight Reduction associated with preventive programs via digital health platform (Auster-Gussman et al., 2022) Patch via Bluetooth (Lin et al., 2019) Watch (Randazzo et al., 2019) Bioprinting of Kidney (Fransen et al., 2021) Chatbots Ask Rosa – Breast & Ovarian Cancer Chatbot (Siglen et al., 2022) HealthBots in Telemedicine (Vasileiou & Maglogiannis, 2022) Bioprinting of Blood Vessels (Wang et al., 2022)
  • 12. Digital Health & AI Healthcare Robots https://www.aldebaran.com/en/blog/news-trends/how-have- humanoid-robots-been-effective-supporting-our-healthcare- workers-during https://www.medicaldevice-network.com/comment/what-are- the-main-types-of-robots-used-in-healthcare/ v Robots reduces Workload and Enhances Healthcare Experience (Kaiser et al., 2021) v Multitasking-Intelligent Nurse Aid (MINA) Robot to reduce nurse burnout (Nambiappan et al., 2021) v CHARMIE Assistant Robot for Elderly Care (Ribeiro et al., 2021)
  • 13. Digital Health Trends deloitte.com/us/en/insights/industry/health-care/digital-health-trends.html telepaxx.com/study-reveals-digital-healthcare-market-grows-faster-than-expected/
  • 14. References Anthony Jnr, B. (2021). Integrating telemedicine to support digital health care for the management of COVID-19 pandemic. https://doi.org/10.1080/20479700.2020.1870354 Auster-Gussman, L. A., Lockwood, K. G., Graham, S. A., Pitter, V., & Branch, O. L. H. (2022). Engagement in Digital Health App-Based Prevention Programs Is Associated With Weight Loss Among Adults Age 65+. Frontiers in Digital Health, 4, 886783. https://doi.org/10.3389/FDGTH.2022.886783 Bengio, Y., Janda, R., Yu, Y. W., Ippolito, D., Jarvie, M., Pilat, D., Struck, B., Krastev, S., & Sharma, A. (2020). The need for privacy with public digital contact tracing during the COVID-19 pandemic. The Lancet Digital Health, 2(7), e342–e344. https://doi.org/10.1016/S2589-7500(20)30133-3 Braithwaite, I., Callender, T., Bullock, M., & Aldridge, R. W. (2020). Automated and partly automated contact tracing: a systematic review to inform the control of COVID- 19. The Lancet Digital Health, 2(11), e607–e621. https://doi.org/10.1016/S2589-7500(20)30184-9 Bruining, N. (2021). The post-pandemic legacy: the breakthrough of digital health and telemedicine. Cardiovascular Research, 117(9), e118–e119. https://doi.org/10.1093/CVR/CVAB178 Chang, A. (2020). The Role of Artificial Intelligence in Digital Health. 71–81. https://doi.org/10.1007/978-3-030-12719-0_7 Cosgriff, C. v., Ebner, D. K., & Celi, L. A. (2020). Data sharing in the era of COVID-19. The Lancet Digital Health, 2(5), e224. https://doi.org/10.1016/S2589-7500(20)30082-0
  • 15. References Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dörner, L., Parker, M., Bonsall, D., & Fraser, C. (2020). Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science (New York, N.Y.), 368(6491). https://doi.org/10.1126/SCIENCE.ABB6936 Frank, S. R. (2000). Digital Health Care—The Convergence of Health Care and the Internet. The Journal of Ambulatory Care Management, 23(2). https://journals.lww.com/ambulatorycaremanagement/Fulltext/2000/04000/Digital_Health_Care_The_Convergence_of_Health_Care.3.aspx Fransen, M. F. J., Addario, G., Bouten, C. V. C., Halary, F., Moroni, L., & Mota, C. (2021). Bioprinting of kidney in vitro models: cells, biomaterials, and manufacturing techniques. Essays in Biochemistry, 65(3), 587–602. https://doi.org/10.1042/EBC20200158 Gasser, U., Ienca, M., Scheibner, J., Sleigh, J., & Vayena, E. (2020). Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid. The Lancet Digital Health, 2(8), e425–e434. https://doi.org/10.1016/S2589-7500(20)30137-0 Gunasekeran, D. v., Tham, Y. C., Ting, D. S. W., Tan, G. S. W., & Wong, T. Y. (2021). Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology. The Lancet Digital Health, 3(2), e124–e134. https://doi.org/10.1016/S2589-7500(20)30287-9 Javaid, M., & Khan, I. H. (2021). Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic. Journal of Oral Biology and Craniofacial Research, 11(2), 209–214. https://doi.org/10.1016/J.JOBCR.2021.01.015
  • 16. References Kaiser, M. S., al Mamun, S., Mahmud, M., & Tania, M. H. (2021). Healthcare Robots to Combat COVID-19. Lecture Notes on Data Engineering and Communications Technologies, 60, 83–97. https://doi.org/10.1007/978-981-15-9682-7_10/COVER Keeling, M. J., Hollingsworth, T. D., & Read, J. M. (2020). Efficacy of contact tracing for the containment of the 2019 novel coronavirus (COVID-19). Journal of Epidemiology and Community Health, 74(10), 861. https://doi.org/10.1136/JECH-2020-214051 Lin, Y. J., Chuang, C. W., Yen, C. Y., Huang, S. H., Huang, P. W., Chen, J. Y., & Lee, S. Y. (2019). Artificial Intelligence of Things Wearable System for Cardiac Disease Detection. Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, 67–70. https://doi.org/10.1109/AICAS.2019.8771630 Loftus ID, T. J., Tighe ID, P. J., Ozrazgat-Baslanti, T. I., Davis, J. P., RuppertID, M. M., RenID, Y., ShickelID, B., KamaleswaranID, R., HoganID, W. R., Randall Moorman, J., Upchurch, G. R., Rashidi, P., & BihoracID, A. (2022). Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible. PLOS Digital Health, 1(1), e0000006. https://doi.org/10.1371/JOURNAL.PDIG.0000006 Marin, A. (2020). Technology Feature | Telemedicine takes center stage in the era of COVID-19. Science, 370(6517), 731–733. https://doi.org/10.1126/SCIENCE.370.6517.731 Mathews, S. C., McShea, M. J., Hanley, C. L., Ravitz, A., Labrique, A. B., & Cohen, A. B. (2019). Digital health: a path to validation. Npj Digital Medicine 2019 2:1, 2(1), 1–9. https://doi.org/10.1038/s41746-019-0111-3
  • 17. References McCall, B. (2020). COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread. The Lancet Digital Health, 2(4), e166–e167. https://doi.org/10.1016/s2589-7500(20)30054-6 Nambiappan, H. R., Kodur, K. C., Kyrarini, M., Makedon, F., & Gans, N. (2021). MINA: A Multitasking Intelligent Nurse Aid Robot. ACM International Conference Proceeding Series, 266–267. https://doi.org/10.1145/3453892.3461010 Omboni, S., Padwal, R. S., Alessa, T., Benczúr, B., Green, B. B., Hubbard, I., Kario, K., Khan, N. A., Konradi, A., Logan, A. G., Lu, Y., Mars, M., McManus, R. J., Melville, S., Neumann, C. L., Parati, G., Renna, N. F., Ryvlin, P., Saner, H., … Wang, J. (2022). The worldwide impact of telemedicine during COVID-19: current evidence and r ecommendations for the future. Connected Health, 1, 7. https://doi.org/10.20517/CH.2021.03 Portnoy, J., Waller, M., & Elliott, T. (2020). Telemedicine in the Era of COVID-19. Journal of Allergy and Clinical Immunology: In Practice, 8(5), 1489–1491. https://doi.org/10.1016/j.jaip.2020.03.008 Randazzo, V., Ferretti, J., & Pasero, E. (2019). ECG WATCH: A real time wireless wearable ECG. Medical Measurements and Applications, MeMeA 2019 - Symposium Proceedings. https://doi.org/10.1109/MEMEA.2019.8802210 Ratta, P., Kaur, A., Sharma, S., Shabaz, M., & Dhiman, G. (2021). Application of Blockchain and Internet of Things in Healthcare and Medical Sector: Applications, Challenges, and Future Perspectives. Journal of Food Quality, 2021. https://doi.org/10.1155/2021/7608296
  • 18. References Ribeiro, T., Gonçalves, F., Garcia, I. S., Lopes, G., & Ribeiro, A. F. (2021). CHARMIE: A Collaborative Healthcare and Home Service and Assistant Robot for Elderly Care. Applied Sciences 2021, Vol. 11, Page 7248, 11(16), 7248. https://doi.org/10.3390/APP11167248 Schwamm, L. H., Estrada, J., Erskine, A., & Licurse, A. (2020). Virtual care: new models of caring for our patients and workforce. The Lancet Digital Health, 2(6), e282– e285. https://doi.org/10.1016/S2589-7500(20)30104-7 Siglen, E., Vetti, H. H., Lunde, A. B. F., Hatlebrekke, T. A., Strømsvik, N., Hamang, A., Hovland, S. T., Rettberg, J. W., Steen, V. M., & Bjorvatn, C. (2022). Ask Rosa – The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer. Patient Education and Counseling, 105(6), 1488– 1494. https://doi.org/10.1016/J.PEC.2021.09.027 The Medical Futurist. (2022). Top 20 Digital Health Trends For The Near Future: 2022-23 Ebook. https://medicalfuturist.com/top-digital-health-trends/ Tilahun, B., Gashu, K. D., Mekonnen, Z. A., Endehabtu, B. F., & Angaw, D. A. (2021). Mapping the Role of Digital Health Technologies in Prevention and Control of COVID- 19 Pandemic: Review of the Literature. Yearbook of Medical Informatics, 30(1), 26–37. https://doi.org/10.1055/S-0041-1726505/ID/JRTILAHUN-43 Tsao, S. F., Chen, H., Tisseverasinghe, T., Yang, Y., Li, L., & Butt, Z. A. (2021). What social media told us in the time of COVID-19: a scoping review. The Lancet Digital Health, 3(3), e175–e194. https://doi.org/10.1016/S2589-7500(20)30315-0 Vasileiou, M. v., & Maglogiannis, I. G. (2022). The Health ChatBots in Telemedicine: Intelligent Dialog System for Remote Support. Journal of Healthcare Engineering, 2022. https://doi.org/10.1155/2022/4876512
  • 19. References Vishnu, S., Jino Ramson, S. R., & Jegan, R. (2020). Internet of Medical Things (IoMT)-An overview. ICDCS 2020 - 2020 5th International Conference on Devices, Circuits and Systems, 101–104. https://doi.org/10.1109/ICDCS48716.2020.243558 Wang, D., Maharjan, S., Kuang, X., Wang, Z., Mille, L. S., Tao, M., Yu, P., Cao, X., Lian, L., Lv, L., He, J. J., Tang, G., Yuk, H., Ozaki, C. K., Zhao, X., & Zhang, Y. S. (2022). Microfluidic bioprinting of tough hydrogel-based vascular conduits for functional blood vessels. Science Advances, 8(43), eabq6900. https://doi.org/10.1126/SCIADV.ABQ6900/SUPPL_FILE/SCIADV.ABQ6900_MOVIES_S1_TO_S6.ZIP Watts, G. (2020). COVID-19 and the digital divide in the UK. The Lancet Digital Health, 2(8), e395–e396. https://doi.org/10.1016/s2589-7500(20)30169-2 Whitelaw, S., Mamas, M. A., Topol, E., & van Spall, H. G. C. (2020). Applications of digital technology in COVID-19 pandemic planning and response. The Lancet Digital Health, 2(8), e435–e440. https://doi.org/10.1016/S2589-7500(20)30142-4 WHO. (2019). Guideline: Recommendations on Digital Interventions for Health System Strengthening: Web Supplement 2: Summary ofFindings and GRADE Tables; World Health Organization. Wilmink, G., Dupey, K., Alkire, S., Grote, J., Zobel, G., Fillit, H. M., & Movva, S. (2020). Artificial Intelligence–Powered Digital Health Platform and Wearable Devices Improve Outcomes for Older Adults in Assisted Living Communities: Pilot Intervention Study. JMIR Aging 2020;3(2):E19554 jttps://Aging.Jmir.Org/2020/2/E19554, 3(2), e19554. https://doi.org/10.2196/19554
  • 20. References Wu, X., Liu, C., Wang, L., & Bilal, M. (2021). Internet of things-enabled real-time health monitoring system using deep learning. Neural Computing and Applications, 1– 12. https://doi.org/10.1007/S00521-021-06440-6/FIGURES/12 Zhou, Y., Wang, F., Tang, J., Nussinov, R., & Cheng, F. (2020). Artificial intelligence in COVID-19 drug repurposing. The Lancet Digital Health, 2(12), e667–e676