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神经学研究和未来实践中的大型语言模型.

Michael F Romano1, Ludy C Shih1, Ioannis C Paschalidis1

  • 1From the Department of Medicine (M.F.R., R.A., V.B.K.), Boston University Chobanian & Avedisian School of Medicine, MA; Department of Radiology and Biomedical Imaging (M.F.R.), University of California, San Francisco; Department of Neurology (L.C.S., R.A.), Boston University Chobanian & Avedisian School of Medicine; Department of Electrical and Computer Engineering (I.C.P.), Division of Systems Engineering, and Department of Biomedical Engineering; Faculty of Computing and Data Sciences (I.C.P., V.B.K.), Boston University; Department of Anatomy and Neurobiology (R.A.); The Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine; Department of Epidemiology, Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (R.A.); and Department of Computer Science (V.B.K.), Boston University, MA.

Neurology
|October 10, 2023
PubMed
概括

大型语言模型 (LLM) 显示了神经学中分析医疗数据的前景,以早期诊断和改善患者护理. 研究人员必须应对道德和技术挑战,以实现负责任的实施.

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