透视图(图形)
工作(物理)
医学
心理学
计算机科学
工程类
人工智能
机械工程
作者
Michael F. Romano,Ludy C. Shih,Ioannis Ch. Paschalidis,Rhoda Au,Vijaya B. Kolachalama
出处
期刊:Neurology
[Ovid Technologies (Wolters Kluwer)]
日期:2023-12-05
卷期号:101 (23): 1058-1067
被引量:8
标识
DOI:10.1212/wnl.0000000000207967
摘要
Recent advancements in generative artificial intelligence, particularly using large language models (LLMs), are gaining increased public attention. We provide a perspective on the potential of LLMs to analyze enormous amounts of data from medical records and gain insights on specific topics in neurology. In addition, we explore use cases for LLMs, such as early diagnosis, supporting patient and caregivers, and acting as an assistant for clinicians. We point to the potential ethical and technical challenges raised by LLMs, such as concerns about privacy and data security, potential biases in the data for model training, and the need for careful validation of results. Researchers must consider these challenges and take steps to address them to ensure that their work is conducted in a safe and responsible manner. Despite these challenges, LLMs offer promising opportunities for improving care and treatment of various neurologic disorders.
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