Abstract Details

Title Localizing Lesions in the Peripheral Nervous System using Generative Artificial Intelligence

Topic General Neurology

Presentation(s) P1 - Poster Session 1 (11:45 AM-12:45 PM)

Poster/Presentation
Number 2-009

Objective Having shown GPT-4’s potential for localizing central nervous system (CNS) lesions, we investigated localization capabilities of GPT-4 in the peripheral nervous system (PNS).

Background Localization of PNS lesions is challenging for non-neurologist healthcare providers, unfamiliar with the variant mappings of nerve roots, upper and lower plexus, and branches of peripheral nerve.

Design/Methods Following our earlier study methods, 51 suitably-detailed open-access case reports were utilized. Unedited text of the history and physical examination (H&P) was manually extracted. Each case input was then presented to GPT-4 in three separate trials to identify consistency of response. We employed our previous prompt engineering, combining: 1. Chain-of-Thought (CoT); 2. Text Classification (TC); 3. Few-shot; 4. Instructional prompting. Statistical analysis identified system specificity, sensitivity, precision, and F1-score.

Results Overall statistics showed: sensitivity 0.97, specificity 0.84, precision 0.97, F1 score 0.97. GPT-4 lesion localization F1 score was 0.98 for spinal cord lesions, 0.97 for spinal root, 0.98 for plexus, 0.91 for peripheral nerve, 0.98 for neuromuscular junction, and 0.96 for muscle. Detailed accuracy for each peripheral lesion localization (e.g., spinal root level) showed 0.60 for the peripheral nerve, 0.72 for the plexus, and 0.86 for the spinal root lesions. Error analysis was mostly due to inaccurate anatomical knowledge, lack of thoroughness, and ignoring relevant neurological findings.

Conclusions Combining results from the previous study of CNS lesion localization through GPT-4 and our study for PNS localization with adequate ability to localize, this could become a useful tool in the clinical setting.

Authors/Disclosures
Minhee Kim, MD, PhD PRESENTER	Dr. Kim has nothing to disclose.
Jung-Hyun Lee, MD (SUNY Downstate Medical Center)	Dr. Lee has nothing to disclose.
Sergio L. Angulo Castro, MD, PhD	Dr. Angulo Castro has nothing to disclose.
Robert McDougal	An immediate family member of Robert McDougal has received personal compensation for serving as an employee of Farnam Real Estate. The institution of Robert McDougal has received research support from NIH. Robert McDougal has a non-compensated relationship as a Webmaster with Organiztion for Computational Neuroscience that is relevant to AAN interests or activities.
William W. Lytton, MD (SUNY Downstate)	Dr. Lytton has nothing to disclose.

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