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GPT-4 Performance for Neurologic Localization.

Jung-Hyun Lee¹, Eunhee Choi¹, Robert McDougal¹

¹Department of Neurology (J-HL, WWL), State University of New York Downstate Health Sciences University; Department of Neurology (J-HL, WWL), Kings County Hospital; Department of Neurology (J-HL), Maimonides Medical Center, Brooklyn; Department of Internal Medicine (EC), Lincoln Medical Center, Bronx, NY; Department of Biostatistics (RM), Yale School of Public Health; Program in Computational Biology and Bioinformatics (RM); Wu-Tsai Institute (RM); Section of Biomedical Informatics and Data Science (RM), Yale School of Medicine, Yale University, New Haven, CT; and Department of Physiology and Pharmacology (WWL), State University of New York Downstate Health Sciences University, Brooklyn, NY.

Neurology. Clinical Practice

|April 10, 2024

Summary

This summary is machine-generated.

Generative Pretrained Transformer-4 (GPT-4) shows promise in localizing acute stroke lesions using clinical data. This advanced AI tool could aid neurologists by accurately identifying lesion locations from patient histories and examinations.

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Area of Science:

Artificial Intelligence in Medicine
Neurology
Medical Imaging Analysis

Background:

Large language models (LLMs) like Generative Pretrained Transformers (GPTs) offer potential to reduce healthcare disparities.
Existing software for lesion localization has limitations in scope.
This study evaluates GPT-4's capability for lesion localization using clinical presentation.

Purpose of the Study:

To assess the accuracy of GPT-4 in localizing acute stroke lesions based on clinical information.
To compare GPT-4's localization performance against imaging-based findings.
To explore the potential of GPT-4 as a clinical tool in neurology.

Main Methods:

GPT-4 was prompted with patient history and neurologic physical examination (H&P) data from acute stroke cases.
Zero-Shot Chain-of-Thought and Text Classification prompting were used for clinical reasoning and localization.
GPT-4's output was compared to imaging-based localization across three trials for 46 cases.

Main Results:

GPT-4 accurately processed H&P text for neuroanatomical localization and clinical reasoning.
Performance metrics (specificity, sensitivity, precision, F1-score) for lesion side and brain region were high.
High accuracy was observed across most brain regions, with minor limitations for the cerebellum.

Conclusions:

GPT-4 demonstrates significant capabilities in localizing acute stroke lesions from clinical data.
The findings suggest a potential future role for GPT-4 as a valuable clinical tool in neurology.
Further research may explore integrating GPT-4 into clinical workflows for stroke diagnosis and management.