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Performance Evaluation of Artificial Intelligence Screening Model in Coronary Heart Disease Detection

NCT06658600 · Status: ACTIVE_NOT_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 900

Last updated 2025-04-08

No results posted yet for this study

Summary

To determine whether an integrated AI decision support can save time and improve accuracy of assessment of obstructive coronary heart disease (CHD), the investigators are conducting a randomized controlled study of AI guided measurements of obstructive CHD probability compared to clinical assessment in preliminary evaluations by physicians.

Conditions

Interventions

OTHER

Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease

Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.

OTHER

Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease

Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.

Sponsors & Collaborators

  • Shanghai Jiao Tong University Affiliated Sixth People's Hospital

    collaborator OTHER

  • Shanghai Health and Medical Center

    collaborator UNKNOWN

  • Tsinghua University

    lead OTHER

Principal Investigators

  • Tien Yin Wong, PhD · Tsinghua University

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-01-10
Primary Completion
2025-04-30
Completion
2025-05-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06658600 on ClinicalTrials.gov