Abstract
As artificial intelligence (AI) tools gain traction in clinical, operational, and administrative settings, healthcare professionals must develop a foundational understanding of key AI concepts to engage with these technologies responsibly and effectively. This perspective outlines essential AI terminology—such as machine learning, generative and agentic AI, large language models, artificial neural networks, and prompt engineering—paired with concrete clinical examples to illustrate their relevance in modern medical practice. By clarifying these terms and exploring their applications, this paper aims to equip healthcare leaders with the vocabulary and context necessary to evaluate, implement, and oversee AI systems within their organizations. Such literacy is critical to ensuring that AI technologies are used ethically, transparently, and in service of improving patient outcomes.
Recommended Citation
Johnson, Teray and Blanchard, Melvin
(2026)
"Artificial Intelligence in Medicine: A Definition of Terms,"
Journal of Community Hospital Internal Medicine Perspectives: Vol. 16:
Iss.
2, Article 1.
DOI: 10.55729/2000-9666.1562
Available at:
https://scholarlycommons.gbmc.org/jchimp/vol16/iss2/1
DOI
10.55729/2000-9666.1562
