FindTrial
Sign In

Evaluation of a technology to predict cover atrial fibrillation in stroke patients using artificial intelligence

Efficacy of artificial intelligence-based potential atrial fibrillation prediction technology in patients with noncardioembolic cerebral infarction

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0010684
Enrollment
250
Registered
2025-06-25
Start date
2023-07-14
Completion date
Unknown
Last updated
2025-07-21

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

Conditions

None listed

Interventions

None listed

Sponsors

Chonnam National University Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: We prospectively constructed the covert atrial fibrillation detection clinical trial by enrolling patients with embolic stroke of undetermined source who consented to the study

Exclusion criteria

Exclusion criteria: Patients were excluded if their brain MRI exhibited metal-induced magnetic susceptibility artifacts that could interfere with deep learning image analysis.

Design outcomes

Primary

MeasureTime frame
atrial fibrillation detection—

Secondary

MeasureTime frame
performance with areas under the curve—

Countries

Korea, Republic of

Contacts

Public ContactKangho Choi

Chonnam National University Hospital

ckhchoikang@hanmail.net+82-62-220-6137

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026