LLMs and Their Applications in Medical Artificial Intelligence

Medical artificial intelligence (AI) is a cross-disciplinary field focused on developing advanced computing and AI technologies to benefit medicine and healthcare. Globally, medical AI has tremendous potential to support the United Nations’ sustainable development goals pertaining to health and well-being. In particular, large language models (LLMs) afford opportunities for positively disrupting medical AI-related research and practice. We present a research framework for LLMs in medical AI. Our framework considers the interplay between health and well-being goals, disease lifecycle stages, and the important emerging role of LLMs in medical AI processes related to various lifecycle stages. As part of our framework, we describe the LLM multiplex—important multimodal, multi-model, multicultural, and multi-responsibility considerations for LLMs in medical AI. We discuss how the five articles in the special issue relate to this framework and are helping us learn about the opportunities and challenges for LLMs in medical AI.

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Publication Details

Journal
ACM Transactions on Management Information Systems
Published
2025-01-09
DOI
https://doi.org/10.1145/3711837
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
8.34
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article

LLMs and Their Applications in Medical Artificial Intelligence

Ahmed Abbasi, Wenji Mao, Xipeng Qiu
2 citations
ACM Transactions on Management Information Systems
Scientific Computing and Data Management
8.34
article

LLMs and Their Applications in Medical Artificial Intelligence

Ahmed Abbasi, Wenji Mao, Xipeng Qiu
article en
2 citations

Abstract

Medical artificial intelligence (AI) is a cross-disciplinary field focused on developing advanced computing and AI technologies to benefit medicine and healthcare. Globally, medical AI has tremendous potential to support the United Nations’ sustainable development goals pertaining to health and well-being. In particular, large language models (LLMs) afford opportunities for positively disrupting medical AI-related research and practice. We present a research framework for LLMs in medical AI. Our framework considers the interplay between health and well-being goals, disease lifecycle stages, and the important emerging role of LLMs in medical AI processes related to various lifecycle stages. As part of our framework, we describe the LLM multiplex—important multimodal, multi-model, multicultural, and multi-responsibility considerations for LLMs in medical AI. We discuss how the five articles in the special issue relate to this framework and are helping us learn about the opportunities and challenges for LLMs in medical AI.

ACM Transactions on Management Information SystemsVol. 16(2)
University of Notre Dame (US), Chinese Academy of Sciences (CN), Fudan University (CN), Shandong Institute of Automation (CN)
Openalex Percentile: Top 4%
Scientific Computing and Data Management
8.34
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LLMs and Their Applications in Medical Artificial Intelligence — Ahmed Abbasi, Wenji Mao, et al. · ACM Transactions on Management Information Systems (2025) | TGRS Research Map | TGRS