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Clinical Development of a Tool for Optimized Self- and Hetero-diagnosis of Stroke Using Artificial Intelligence: Stage1- Collection of Video-clinical Data in a Pragmatic Situation.

NCT05959746 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 300

Last updated 2024-11-27

No results posted yet for this study

Summary

The study authors aim to form a collection of video-clinical data in a pragmatic situation to enable the development of relevant AI algorithms (for both hetero- and self-diagnosis modes). The aim is to optimize management through early diagnosis (self- and hetero-diagnosis) and thus to reduce sequelae disability.

The study authors hypothesize that some stroke patients will be able to successfully perform a self-test consisting of a few exercises dictated by an application on a smartphone or tablet and recorded on video.

Conditions

  • Stroke, Cerebrovascular

Interventions

OTHER

AI-STROKE application

Complete neurological exam of stroke patients will be filmed by healthcare workers and themselves using the AI-STROKE application

Sponsors & Collaborators

  • Société par Action Simplifiée AI-Stroke

    collaborator UNKNOWN

  • Centre Hospitalier Universitaire de Nīmes

    lead OTHER

Principal Investigators

  • Anne WACONGNE · CHU de Nimes

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-28
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05959746 on ClinicalTrials.gov