Large Language Models for Epidural Stimulation Electrode Mapping in Spinal Cord Injury
2026년 9월 8일 업데이트: Görkem Açar, Istanbul Gelisim University
AI-Assisted Electrode Contact Configuration Mapping for Epidural Electrical Stimulation in Spinal Cord Injury: A Comparative Evaluation of Large Language Models
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.
연구 개요
상태
모집하지 않고 적극적으로
정황
연구 유형
관찰
등록 (실제)
20
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 장소
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Istanbul
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Istanbul, Istanbul, 터키 (Türkiye), 34290
- Istanbul Gelisim University
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참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
공부할 수 있는 나이
- 어린이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
아니
샘플링 방법
비확률 샘플
연구 인구
No human study population is included.
The analytical sample consists of five standardized synthetic spinal cord injury scenarios and the responses generated for these scenarios by ChatGPT-4o, Claude, Grok 3, and Gemini 2.5 Pro.
Each model is evaluated under the same standardized prompting conditions.
Model outputs are anonymized and independently rated by expert evaluators for clinical accuracy, technical feasibility, safety awareness, consistency with clinical guidance, and response completeness.
설명
Inclusion Criteria:
- Responses generated for one of the five predefined standardized synthetic spinal cord injury scenarios.
- Responses generated using the identical standardized prompt specified in the study protocol.
- Responses generated by one of the four prespecified large language models.
- Complete responses available for expert evaluation.
Exclusion Criteria:
- Responses generated using prompts that differ from the standardized study prompt.
- Incomplete, interrupted, or technically corrupted model outputs.
- Duplicate responses or outputs not corresponding to a predefined synthetic scenario.
- Any response generated using real patient-identifiable or personal health information.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
코호트 및 개입
그룹/코호트 |
개입 / 치료 |
|---|---|
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ChatGPT-4o
Responses generated by ChatGPT-4o for five standardized synthetic spinal cord injury scenarios using the same standardized prompt.
The responses will be evaluated for clinical accuracy, technical feasibility, safety awareness, guideline consistency, and completeness.
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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.
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Claude
Responses generated by Claude for five standardized synthetic spinal cord injury scenarios using the same standardized prompt.
The responses will be evaluated for clinical accuracy, technical feasibility, safety awareness, guideline consistency, and completeness.
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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.
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Grok 3
Responses generated by Grok 3 for five standardized synthetic spinal cord injury scenarios using the same standardized prompt.
The responses will be evaluated for clinical accuracy, technical feasibility, safety awareness, guideline consistency, and completeness.
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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.
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Gemini 2.5 Pro
Responses generated by Grok 3 for five standardized synthetic spinal cord injury scenarios using the same standardized prompt.
The responses will be evaluated for clinical accuracy, technical feasibility, safety awareness, guideline consistency, and completeness.
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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.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Clinical Accuracy Score of Large Language Model Responses
기간: At the time of expert evaluation, within 1 week after study initiation
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Clinical accuracy of the epidural electrical stimulation electrode contact configuration recommendations generated by each large language model will be independently evaluated by expert reviewers using a 5-point Likert-type rating scale.
Higher scores indicate greater clinical accuracy of the generated recommendations.
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At the time of expert evaluation, within 1 week after study initiation
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Technical Feasibility Score of Large Language Model Responses
기간: At expert evaluation, within 1 week after study initiation
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The technical feasibility of epidural electrical stimulation electrode contact configuration recommendations generated by each large language model will be independently evaluated by expert reviewers using a 5-point Likert-type rating scale.
Higher scores indicate greater technical feasibility and applicability of the generated recommendations.
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At expert evaluation, within 1 week after study initiation
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Safety Awareness Score of Large Language Model Responses
기간: At expert evaluation, within 1 week after study initiation
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The safety awareness demonstrated in the epidural electrical stimulation electrode contact configuration recommendations generated by each large language model will be independently evaluated by expert reviewers using a 5-point Likert-type rating scale.
Higher scores indicate greater recognition and consideration of relevant safety issues.
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At expert evaluation, within 1 week after study initiation
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Clinical Guideline Consistency Score of Large Language Model Responses
기간: At expert evaluation, within 1 week after study initiation
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The consistency of the generated epidural electrical stimulation electrode contact configuration recommendations with current clinical guidance will be independently evaluated by expert reviewers using a 5-point Likert-type rating scale.
Higher scores indicate greater consistency with current clinical guidance and relevant evidence-based recommendations.
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At expert evaluation, within 1 week after study initiation
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Response Completeness Score of Large Language Model Responses
기간: At expert evaluation, within 1 week after study initiation
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The completeness of the epidural electrical stimulation electrode contact configuration recommendations generated by each large language model will be independently evaluated by expert reviewers using a 5-point Likert-type rating scale.
Higher scores indicate more complete and comprehensive responses.
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At expert evaluation, within 1 week after study initiation
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공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
2026년 9월 2일
기본 완료 (추정된)
2026년 9월 9일
연구 완료 (추정된)
2026년 9월 9일
연구 등록 날짜
최초 제출
2026년 9월 8일
QC 기준을 충족하는 최초 제출
2026년 9월 8일
처음 게시됨 (실제)
2026년 9월 14일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
2026년 9월 14일
QC 기준을 충족하는 마지막 업데이트 제출
2026년 9월 8일
마지막으로 확인됨
2026년 9월 1일
추가 정보
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .