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Training Radiologists to Understand Statistical Pitfalls in AI for Cerebral Aneurysm Detection

Training Radiologists to Understand Statistical Pitfalls in AI for Cerebral Aneurysm Detection

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
DRKS
Registry ID
DRKS00038740
Enrollment
30
Registered
2025-12-16
Start date
2025-12-15
Completion date
Unknown
Last updated
2026-01-12

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

Conditions

I67.1

Interventions

Group 1: Intervention group: Participants initially review a video tutorial on the Accuracy Paradox. Subsequently, they evaluate 20 TOF-MRA examinations for the presence of cerebral aneurysms with AI

Sponsors

Technische Universität München
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: Inclusion criteria patients: Retrospective identification of head MRI studies with positive AI aneurysm finding. Age above 18 years. Inclusion criteria radiologists: at least 6 months of experience in reading brain MRI studies.

Exclusion criteria

Exclusion criteria: Exclusion criteria patients: Insufficient MRI image quality

Design outcomes

Primary

MeasureTime frame
Frequency of cases where a false positive AI finding is accepted Frequency of cases where a follow-up examination is recommended for a false positive AI finding

Secondary

MeasureTime frame
Frequency of AI-negative lesions rated as aneurysm Level of confidence

Countries

Germany

Contacts

Public ContactSu Hwan Kim

Technische Universität München

suhwan.kim@tum.de+498941408834

Outcome results

None listed

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