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Large Language Models for Epidural Stimulation Electrode Mapping in Spinal Cord Injury
Sponsor: Istanbul Gelisim University
Summary
This observational and methodological study aims to compare the performance of large language models in generating electrode contact configuration recommendations for epidural electrical stimulation in spinal cord injury. Five standardized synthetic spinal cord injury scenarios will be presented to four large language models: ChatGPT-4o, Claude, Grok 3, and Gemini 2.5 Pro. Each model will receive the same standardized prompt. The generated responses will be anonymized and evaluated independently by experts with experience in spinal cord injury rehabilitation and epidural electrical stimulation. The responses will be assessed in five main areas: clinical accuracy, technical feasibility, safety awareness, consistency with current clinical guidance, and completeness of the response. Agreement between expert evaluators will also be examined. No real patients, human participants, clinical interventions, or personal health data are included in this study. The study is designed to explore the potential and current limitations of large language models as artificial intelligence-based clinical decision-support tools in neurorehabilitation.
Official title: AI-Assisted Electrode Contact Configuration Mapping for Epidural Electrical Stimulation in Spinal Cord Injury: A Comparative Evaluation of Large Language Models
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
20
Start Date
2026-09-02
Completion Date
2026-09-09
Last Updated
2026-09-14
Healthy Volunteers
No
Conditions
Interventions
ChatGPT-4o Large Language Model
The large language model receives five standardized synthetic spinal cord injury scenarios using an identical standardized prompt and generates recommendations for epidural electrical stimulation electrode contact configuration mapping. No intervention is administered to human participants.
Claude Large Language Model
The large language model receives five standardized synthetic spinal cord injury scenarios using an identical standardized prompt and generates recommendations for epidural electrical stimulation electrode contact configuration mapping. No intervention is administered to human participants.
Grok 3 Large Language Model
The large language model receives five standardized synthetic spinal cord injury scenarios using an identical standardized prompt and generates recommendations for epidural electrical stimulation electrode contact configuration mapping. No intervention is administered to human participants.
Gemini 2.5 Pro Large Language Model
The large language model receives five standardized synthetic spinal cord injury scenarios using an identical standardized prompt and generates recommendations for epidural electrical stimulation electrode contact configuration mapping. No intervention is administered to human participants.
Locations (1)
Istanbul Gelisim University
Istanbul, Istanbul, Turkey (Türkiye)