AI in Healthcare: 40 Essential Terms for Clinical Understanding and Real-World Practice
Year: 2025
Type: article
Abstract: This guide provides a practical and accessible introduction to artificial intelligence in healthcare through 40 essential terms that go beyond simple definitions. Designed as a bridge between technical complexity and clinical practice, it translates core AI ideas into real-world healthcare contexts using scenario-based explanations, pro tips, and myth-busters. Covering foundational AI concepts, healthcare data and infrastructure, clinical applications, and ethics and governance, the guide equips clinicians, healthcare professionals, students, and decision-makers with a clear and structured understanding of how AI is used across the healthcare ecosystem. It highlights not only what these concepts mean, but how they impact diagnosis, treatment, workflows, and patient outcomes in everyday care settings. Unlike traditional glossaries, this resource emphasizes practical understanding over terminology, enabling readers to interpret AI-driven systems, question outputs, and engage more confidently with digital health technologies. It reinforces that AI in healthcare is not just about algorithms, but about data quality, clinical context, human oversight, and responsible implementation. Part of the HealthInnovation Toolbox Innovation Series, this guide serves as a foundational learning resource for building AI literacy in healthcare, supporting safer adoption, better decision-making, and more equitable, technology-enabled care systems.
Authors: Sonu, Monika, Chakraborty, Kingshuk
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7149558282