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NCT06851429

Ovarian Cancer Identification on CT Using Deep Learning

Active, enrolled Last updated 28 February 2025
What this trial tests

trial in Ovarian Cancer in 12,578 participants. Participants enrolled and being followed up; not accepting new ones.

Timeline
1 September 2022
Primary endpoint
7 February 2025
28 February 2025

Quick facts

Lead sponsorChang Gung Memorial Hospital
StatusActive, enrolled
Study typeOBSERVATIONAL
Enrollment12,578
Start date1 September 2022
Primary completion7 February 2025
Estimated completion28 February 2025
Sites1 location across Taiwan

Conditions studied

Sponsor

Chang Gung Memorial Hospital

Who can join

20 and older, female only, with Ovarian Cancer. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Ovarian cancer remains the deadliest gynecologic malignancy, with poor survival rates largely due to late-stage diagnosis. Early detection is crucial, yet no universally accepted screening method exists. Current imaging techniques and biomarkers, such as CA-125, have limitations in specificity and sensitivity. This study aims to develop and evaluate a deep learning-based computer-aided diagnosis tool (CAT-OV), for ovarian cancer detection using CT imaging. The system integrates a Body Part Regression (BPR) model for pelvic localization and a Multiple Instance Learning (MIL) ensemble classifier for cancer prediction. The model was trained and validated using retrospective datasets from Taiwan, the United States, and a nationwide real-world cohort. Stringent preprocessing and quality control measures were implemented to enhance model accuracy. Results highlight the potential of AI-driven CT screening in improving early detection, though further validation is needed for clinical adoption.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Ovarian Cancer

Currently open trials in the same condition.

Other Chang Gung Memorial Hospital trials

Trials by the same sponsor.

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06851429.

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