全球公平编码中的患者能动性与大语言模型
Patient agency and large language models in worldwide encoding of equity.
作者信息
Armoundas Antonis A, Loscalzo Joseph
机构信息
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Broad Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
出版信息
NPJ Digit Med. 2025 May 8;8(1):258. doi: 10.1038/s41746-025-01598-y.
Abstract
Large language models progressively result in improved ways of patient engagement and access to healthcare, reaching both an exciting and concerning time, as they no longer serve solely as a guide to clinicians, but, for the first time enable patients to make decisions that directly affect their health. We present the benefits and risks of this paradigm-shift in the practice of medicine, that offers the possibility of promoting health equity.
摘要
大语言模型逐渐带来了改善患者参与度和获得医疗保健的方式，这正处于一个既令人兴奋又令人担忧的时期，因为它们不再仅仅作为临床医生的指导工具，而是首次使患者能够做出直接影响自身健康的决策。我们阐述了医学实践中这种范式转变的益处和风险，它提供了促进健康公平的可能性。
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