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首页|期刊导航|Neural Regeneration Research|From text to image:challenges in integrating vision into ChatGPT for medical image interpretation

From text to image:challenges in integrating vision into ChatGPT for medical image interpretationOA

中文摘要

Large language models(LLMs),such as ChatGPT developed by OpenAI,represent a significant advancement in artificial intelligence(AI),designed to understand,generate,and interpret human language by analyzing extensive text data.Their potential integration into clinical settings offers a promising avenue that could transform clinical diagnosis and decision-making processes in the future(Thirunavukarasu et al.,2023).This article aims to provide an in-depth analysis of LLMs’current and potential impact on clinical practices.Their ability to generate differential diagnosis lists underscores their potential as invaluable tools in medical practice and education(Hirosawa et al.,2023;Koga et al.,2023).

Shunsuke Koga;Wei Du;

Department of Pathology and Laboratory Medicine,Hospital of the University of Pennsylvania,Philadelphia,PA,USA

语言文学

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《Neural Regeneration Research》 2025 (002)

P.487-488 / 2

10.4103/NRR.NRR-D-24-00165

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