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.

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorCentre Hospitalier Universitaire de Nīmes

About this trial

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.

Eligibility criteria

Qualifiers

Patients treated in the emergency department or hospitalized in the NICU at the CHU de Nîmes for suspected stroke or transient ischemic attack in the acute phase (<72h), with or without motor deficit

Patient to be seen again in consultation within 4 months

Patient has given free and informed consent and signed the consent form. If the patient is not in a position to give consent, it must be obtained, prior to filming the first video, from the designated trusted support person or relatives present. In this case, data will not be used until the patient is able to sign the consent (CNIL).

Patient affiliated or beneficiary of a health insurance scheme

Disqualifiers

Patients who do not speak or read French.

Patient in a period of exclusion determined by another study.

Patient under court protection, guardianship or curatorship.

Pregnant, parturient or breast-feeding patients.

Trial design

Treatments tested in this trial

  • AI-STROKE application

Treatment groups

300 Participants
are divided into 1 treatment group

Sponsors and collaborators

Centre Hospitalier Universitaire de Nīmes

Lead sponsor

Société par Action Simplifiée AI-Stroke

Collaborator