The Role of Artificial Intelligence in Digital Health

  • Anthony Chang
Part of the Health Informatics book series (HI)


Digital medicine and health herald the era of technological advances such as apps, wearable technology and remote monitoring, telemedicine and communication tools, and other diagnostic devices to affect a more optimal quality of care as well as a more timely response to any situation. The overarching theme in digital health and medicine in the use of AI in orchestrating, storing, and interpreting the huge amounts of data derived from the devices to facilitate acute and chronic disease diagnosis and management via AI-enabled acquisition and interpretation of data. This strategy will both increase the ability to proactively intervene when appropriate as well as decrease the burden on both the patient and the caretakers when the decisions are relatively straightforward.

In the near future, embedded AI (eAI) and machine learning algorithms evolve toward the internet of everything (IoE) and will bring together people, process, data, and things; this strategy will allow the accrued data to be streamlined and organized in the cloud proactively in an overall paradigm of personalized precision medicine. As these devices become more intelligent, increasingly higher levels of sophistication in decision support can also be part of both (1) preventive medicine (such as retinal images for retinopathy screening or skin lesions for melanoma detection) as well as (2) chronic disease care management (such as diabetes, hypertension, or heart failure).


Artificial intelligence Digital medicine Wearable technology Apps Telemedicine Telehealth Bid data Machine learning Deep learning Natural language processing Cognitive computing Internet of things Internet of everything 



I would like to express my deep gratitude to Ms. Audrey He, my research assistant, for her tireless dedication and utmost support for the work on this chapter.


  1. 1.
    Turing AM. On computable numbers, with an application to the Entscheidungsproblem. Proc Lond Math Soc. 1937;S2–42(1):230–65.CrossRefGoogle Scholar
  2. 2.
    Copeland J. The essential turing. Oxford: Oxford University Press; 2004.Google Scholar
  3. 3.
    Shortliffe EH, David R, Axline SG, et al. Computer-based consultations in clinical therapeutics: explanation and rule acquisition capabilities of the MYCIN system. Comput Biomed Res. 1975;8(4):303–20.CrossRefGoogle Scholar
  4. 4.
    Chen Y, Argentinis E, Weber G. IBM Watson: how cognitive computing can be applied to big data challenges in life and science research. Clin Ther. 2016;38(4):688–701.CrossRefGoogle Scholar
  5. 5.
    Gunning D. Talk at DARPA. 2016.Google Scholar
  6. 6.
    Krizhevsky A, Sututskever I, Hinto GE. ImageNet classification withDeep convolutional neural networks, vol. 1. La Jolla, CA: Neural Information Processing Systems Foundation Inc; 2012. p. 4.Google Scholar
  7. 7.
    LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44.CrossRefGoogle Scholar
  8. 8.
    Porter J, editor. Deep learning: fundamentals, methods, and applications. New York: Nova Science Publishers; 2016.Google Scholar
  9. 9.
    Arel I, Rose DC, Kanowski TP. Deep machine learning—a new frontier in artificial intelligence research. IEEE Comput Intell Mag. 2010;5:13–8. 1556-603X.CrossRefGoogle Scholar
  10. 10.
    Groopman J. How doctors think. Boston: Houghton Mifflin; 2007.Google Scholar
  11. 11.
    Kahneman D. Thinking, fast and slow. New York: Farrar, Straus, and Giroux; 2011.Google Scholar
  12. 12.
    Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ. 2005;330:781–3.CrossRefGoogle Scholar
  13. 13.
    Chang AC, et al. Artificial intelligence in pediatric cardiology: an innovative transformation in patient care, clinical research, and medical education. Cong Card Today. 2012;10:1–12.Google Scholar
  14. 14.
    Roski J, et al. Creating value in health care through big data: opportunities and policy implications. Health Aff. 2014;33(7):1115–22.CrossRefGoogle Scholar
  15. 15.
    Weil AR. Big data in health: a new era for research and patient care. Health Aff. 2014;33:1110.CrossRefGoogle Scholar
  16. 16.
    Healthcare Content Management White Paper. Unstructured data in electronic health record (HER) systems: challenges and solutions. 2013.
  17. 17.
    Hughes G. How big is “Big Data” in healthcare? SAS Blogs. 2011.Google Scholar
  18. 18.
    Jee K, et al. Potentiality of big data in the medical sector: focus on how to reshape the healthcare system. Healthc Infrom Res. 2013;19(2):79–85.CrossRefGoogle Scholar
  19. 19.
    Schneeweiss S. Learning from big health care data. N Engl J Med. 2014;370:2161–3.CrossRefGoogle Scholar
  20. 20.
    Bates DW, et al. Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. 2014;7(2014):1123–31.CrossRefGoogle Scholar
  21. 21.
    Feero WG, et al. Review article: genomic medicine—an updated primer. N Engl J Med. 2010;362:2001–11.CrossRefGoogle Scholar
  22. 22.
    Chan M, et al. Smart wearable systems: current status and future challenges. Artif Intell Med. 2012;56(3):137–56.CrossRefGoogle Scholar
  23. 23.
    Banaee H, Ahmed MU, Loutfi A. Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges. Sensors (Basel). 2013;13(12):17472–500.CrossRefGoogle Scholar
  24. 24.
    Steinhubl SR, Topol EJ. Moving from digitalization to digitization in cardiovascular care: why is it important, and why could it mean for patients and providers? J Am Coll Cardiol. 2015;66(13):1489–96.CrossRefGoogle Scholar
  25. 25.
    Kubota KJ, Chen JA, Little MA. Machine learning for large-scale wearable sensor data in parkinson’s disease: concepts, promises, pitfalls, and features. Mov Disord. 2016;31(9):1314–26.CrossRefGoogle Scholar
  26. 26.
    Is digital medicine different? Editorial in Lancet. 2018;392:95.Google Scholar
  27. 27.
    Fogel AL, Kvedar JC. Perspective: artificial intelligence powers digital medicine. NPJ Digit Med. 2018;1:5–8.CrossRefGoogle Scholar
  28. 28.
    Dimitrov D. Medical internet of things and big data in healthcare. Healthc Inform Res. 2016;22(3):156–63.CrossRefGoogle Scholar
  29. 29.
    Fatehi F, Menon A, Bird D. Diabetes care in the digital era: a synoptic overview. Curr Diab Rep. 2018;18(7):38–47.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Anthony Chang
    • 1
  1. 1.The Sharon Disney Lund Medical Intelligence and Innovation Institute (MI3), Children’s Hospital of Orange CountyOrangeUSA

Personalised recommendations