FindTrial
Sign In

Identification of cardiogenic stroke and risk stratification by artificial intelligence technology

Use of artificial intelligence-assisted MRI images to identify underlying atrial fibrillation after ischemic stroke

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200056385
Enrollment
Unknown
Registered
2022-02-04
Start date
2022-04-25
Completion date
Unknown
Last updated
2024-09-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

cardioembolic stroke

Interventions

atrial fibrillation related stroke:none
Non atrial fibrillation related stroke:none

Sponsors

Shanghai Jiao Tong University Affiliated Sixth People’s Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: ? Diagnosed as acute ischemic stroke ? Received MRI examination and identified infarcted lesions in DWI sequence ? Complete AF assessment after admission, including admission electrocardiogram, at least 24 hours Holter electrocardiogram testing, and/or transesophageal ultrasound (TTE) ? Complete clinical data and follow-up information available

Exclusion criteria

Exclusion criteria: ? Poor MRI image quality ? Transient ischemic attack or no recognizable lesions on DWI sequence ? Heart valve disease ? Incomplete AF evaluation

Design outcomes

Primary

MeasureTime frame
Accuracy of AI model in classifying patient AF status;—

Secondary

MeasureTime frame
Attention mechanism of AI model;—

Countries

China

Contacts

Public ContactHuang Dong

Shanghai Jiao Tong University Affiliated Sixth People’s Hospital

Huangdong1004@126.com+86 189 3017 3998

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 6, 2026