- ICH GCP
- Реестр клинических исследований США
- Клиническое испытание NCT07817238
Large Language Models for Epidural Stimulation Electrode Mapping in Spinal Cord Injury
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.
Обзор исследования
Статус
Условия
Тип исследования
Регистрация (Действительный)
Контакты и местонахождение
Места учебы
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Istanbul
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Istanbul, Istanbul, Турция (Туркие), 34290
- Istanbul Gelisim University
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Критерии участия
Критерии приемлемости
Возраст, подходящий для обучения
- Ребенок
- Взрослый
- Пожилой взрослый
Принимает здоровых добровольцев
Метод выборки
Исследуемая популяция
Описание
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.
Учебный план
Как устроено исследование?
Детали дизайна
Когорты и вмешательства
Группа / когорта |
Вмешательство/лечение |
|---|---|
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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.
|
|
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.
|
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
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.
|
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
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.
|
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.
|
Что измеряет исследование?
Первичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Clinical Accuracy Score of Large Language Model Responses
Временное ограничение: 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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Вторичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
|
Technical Feasibility Score of Large Language Model Responses
Временное ограничение: At expert evaluation, within 1 week after study initiation
|
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
Временное ограничение: At expert evaluation, within 1 week after study initiation
|
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
Временное ограничение: At expert evaluation, within 1 week after study initiation
|
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
Временное ограничение: At expert evaluation, within 1 week after study initiation
|
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
|
Соавторы и исследователи
Спонсор
Даты записи исследования
Изучение основных дат
Начало исследования (Действительный)
Первичное завершение (Оцененный)
Завершение исследования (Оцененный)
Даты регистрации исследования
Первый отправленный
Впервые представлено, что соответствует критериям контроля качества
Первый опубликованный (Действительный)
Обновления учебных записей
Последнее опубликованное обновление (Действительный)
Последнее отправленное обновление, отвечающее критериям контроля качества
Последняя проверка
Дополнительная информация
Термины, связанные с этим исследованием
Дополнительные соответствующие термины MeSH
Другие идентификационные номера исследования
- EES-LLM-2026-01
Информация о лекарствах и устройствах, исследовательские документы
Изучает лекарственный продукт, регулируемый FDA США.
Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.
Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .