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Using Artificial Intelligence to Detect Blockages in Blood Vessels of the heart from CT Scan Images

Development and validation of Deep Learning Model to diagnose Coronary Artery Disease from Computed Tomography Coronary Angiography Images - NIL

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2024/07/070754
Enrollment
3000
Registered
2024-07-16
Start date
Unknown
Completion date
Unknown
Last updated
2026-09-14

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

Conditions

Health Condition 1: I20-I25- Ischemic heart diseases

Interventions

Intervention1: NIL: NIL Control Intervention1: NIL: NIL

Sponsors

Manipal Academy of Higher Education Manipal
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Adult patients (more than 18 years of age) who have undergone CTCA in the last 10 years for diagnosis of CAD.

Exclusion criteria

Exclusion criteria: Patients with poor quality CTCA images.

Design outcomes

Primary

MeasureTime frame
Accuracy of deep learning AI image classification model in diagnosing CADTimepoint: Baseline—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactGanesh Paramasivam

Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal

ganesh.p@manipal.edu9914204224

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Sep 19, 2026