Generative AI in healthcare: foundations, applications, challenges and future directions

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Authors: Jiamin Zheng, Bo Li, Hongmei Li, Yang Lu
Cited by: 1
References: 142

Abstract

Generative AI, as a key technology driving the digital transformation of the medical system, is reshaping the processing and application models of medical information. This study conducts a review on the technical foundation, application scenarios, key challenges, and future development trends of Generative AI in healthcare. Although Generative AI demonstrates value in information processing, decision support, and patient services, its actual deployment is concentrated in low-risk areas. The application of Generative AI in high-risk clinical scenarios is limited by the lack of technical reliability, organizational acceptance, and regulatory frameworks. Generative AI could be regarded as an auxiliary and human-oriented technological tool rather than as an autonomous system that replaces clinical professional judgment. The long-term impact of Generative AI in healthcare will depend on whether it can truly meet clinical practical needs. Through a governance model and a human-oriented implementation path, the true integration of Generative AI and the healthcare system can be achieved.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Machine Learning in Healthcare Explainable Artificial Intelligence (XAI)

Publication details

Journal / source
Journal of Management Analytics
Publisher
Informa UK Limited
Volume
13
Issue
2
Pages
350–378
Publication date
3 April 2026
Language
EN