Previous Chapter: Appendix D: Workshop Materials
Suggested Citation: "Appendix E: Glossary of Terms." National Academies of Sciences, Engineering, and Medicine. 2023. Artificial Intelligence in Health Professions Education: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/27174.

Appendix E

Glossary of Terms

Artificial intelligence (AI) is an umbrella term that means the use of computers to perform tasks that typically require objective reasoning and understanding (Thomason, 2020).

Artificial neural networks are a set of algorithms that mimic the human brain (Kavlakoglu, 2020).

Deep learning is a technique within machine learning in which artificial neural networks are used to solve complex clinical problems (Sarker, 2021).

Interoperability has multiple definitions, including the following:

  • The ability of information to be shared and used seamlessly across medical devices and systems to improve health and care coordination (Center for Medical Interoperability, 2021).
  • Enablement of the secure exchange of electronic health information with, and use of electronic health information from, other health information technology without special effort on the part of the user; [and] allows for complete access, exchange, and use of all electronically accessible health information for authorized use under applicable state or federal law (ONC and HHS, 2020).

Machine learning (ML) is defined as the “use of statistical and mathematical modeling techniques that use a variety of approaches to automatically

Suggested Citation: "Appendix E: Glossary of Terms." National Academies of Sciences, Engineering, and Medicine. 2023. Artificial Intelligence in Health Professions Education: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/27174.

learn and improve the prediction of a target state without explicit programming” (Matheny et al., 2019).

REFERENCES

Center for Medical Interoperability. 2021. Home page. https://medicalinteroperability.org/ (accessed May 18, 2023).

Kavlakoglu, E. 2020. AI vs. machine learning vs. deep learning vs. neural networks: What’s the difference? IBM, May 27. https://www.ibm.com/cloud/blog/ai-vs-machine-learning-vs-deep-learning-vs-neural-networks (accessed June 23, 2023).

Matheny, M., S. Thadaney Israni, M. Ahmed, and D. Whicher (eds.). 2019. Artificial intelligence in health care: The hope, the hype, the promise, the peril. National Academy of Medicine special publication. Washington, DC: National Academy of Medicine.

ONC and HHS (Office of the National Coordinator for Health Information Technology and the Department of Health and Human Services). 2020. 21st Century Cures Act: Interoperability, information blocking, and the ONC Health IT Certification Program. https://www.federalregister.gov/d/2020-07419/p-42de (accessed June 23, 2023).

Sarker, I. H. 2021. Deep learning: A comprehensive overview on techniques, taxonomy, applications and research directions. SN Computer Science 2:420. (2021). https://doi.org/10.1007/s42979-021-00815-1.

Thomason, R. 2020. Logic and artificial intelligence. The Stanford Encyclopedia of Philosophy Summer. E. N. Zalta (ed.). https://plato.stanford.edu/archives/sum2020/entries/logic-ai/>. (accessed June 23, 2023).

Suggested Citation: "Appendix E: Glossary of Terms." National Academies of Sciences, Engineering, and Medicine. 2023. Artificial Intelligence in Health Professions Education: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/27174.
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Suggested Citation: "Appendix E: Glossary of Terms." National Academies of Sciences, Engineering, and Medicine. 2023. Artificial Intelligence in Health Professions Education: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/27174.
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