Academic Journal
Large Language Models in Neurology Research and Future Practice.
| Τίτλος: | Large Language Models in Neurology Research and Future Practice. |
|---|---|
| Συγγραφείς: | Romano MF; From 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., Shih LC; From 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., Paschalidis IC; From 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., Au R; From 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., Kolachalama VB; From 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. vkola@bu.edu. |
| Πηγή: | Neurology [Neurology] 2023 Dec 04; Vol. 101 (23), pp. 1058-1067. Date of Electronic Publication: 2023 Dec 04. |
| Τύπος έκδοσης: | Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, N.I.H., Extramural |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0401060 Publication Model: Electronic Cited Medium: Internet ISSN: 1526-632X (Electronic) Linking ISSN: 00283878 NLM ISO Abbreviation: Neurology Subsets: MEDLINE |
| Imprint Name(s): | Publication: Hagerstown, MD : Lippincott Williams & Wilkins Original Publication: Minneapolis. |
| Ιατρικοί όροι (MeSH): | Artificial Intelligence* , Neurology*, Humans ; Language ; Medical Records ; Research Personnel |
| Περίληψη: | 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. (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.) |
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| Grant Information: | RF1 AG062109 United States AG NIA NIH HHS; R01 HL159620 United States HL NHLBI NIH HHS; R21 CA253498 United States CA NCI NIH HHS; R43 DK134273 United States DK NIDDK NIH HHS; RF1 AG072654 United States AG NIA NIH HHS; U19 AG068753 United States AG NIA NIH HHS; P30 AG013846 United States AG NIA NIH HHS |
| Entry Date(s): | Date Created: 20231010 Date Completed: 20231206 Latest Revision: 20260922 |
| Update Code: | 20260922 |
| PubMed Central ID: | PMC10752640 |
| DOI: | 10.1212/WNL.0000000000207967 |
| PMID: | 37816646 |
| Βάση Δεδομένων: | MEDLINE |
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