Clinical Validation of an Artificial Intelligence-Based G-FAST Score in Patients With Stroke
Starting soon
Conditions studied: Stroke
In brief
This study aims to validate the clinical performance of an artificial intelligence (AI)-based automatic assessment system for the G-FAST score. The core comparison is the consistency and accuracy between AI-generated G-FAST results and standardized manual G-FAST assessments performed by trained professionals. The goal is to provide a convenient, efficient, and objective tool for acute stroke screening and early identification, reduce the subjective variability of manual scoring, and optimize the pre-hospital and in-hospital stroke assessment workflow.
Key facts
- Study ID
- NCT07538492
- Run by
- Xuanwu Hospital, Beijing
- People needed
- 297
- Starts
- 2026-04-10
- Expected to finish
- 2028-12-31
- Last updated by the study team
- 2026-04-20
Who can join
Age: 18 and older. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Aged ≥ 18 years, of either sex.
- Clinically diagnosed with stroke, and confirmed by cranial CT/MRI to have ischemic or hemorrhagic stroke.
- Onset within 7 days.
- Alert and oriented, able to cooperate with standardized video and audio data collection.
- The patient or their legally authorized representative understands the study and voluntarily provides written informed consent (including consent for audio-visual data collection).
You may not qualify if…
- Neurological deficits caused by non-stroke etiologies (e.g., brain tumor, traumatic brain injury, encephalitis).
- Patients with impaired consciousness, severe cognitive dysfunction, or psychiatric disorders that prevent cooperation with video collection and scale assessment.
- Patients with severe visual or hearing impairment, or global aphasia, who are unable to follow instructions.
- Critically ill patients requiring immediate cardiopulmonary resuscitation or endotracheal intubation, making video and audio data collection impossible.
- Patients with severe facial or limb deformities, or large-area dressings that severely interfere with camera data collection.
- Patients with unilateral or bilateral upper limb amputation, severe deformity, unhealed fracture, joint fixation, or severe contracture.
Full record on ClinicalTrials.gov
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