Development and Application of a Deep Learning Diagnostic Model for Borderline Ovarian Tumors

Status

Recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2500108978

Enrollment

Unknown

Registered

2025-09-10

Start date

2025-09-10

Completion date

Unknown

Last updated

2025-09-15

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

Conditions

ovarian tumor

Interventions

Case group:None

Eligibility

Sex/Gender

Female

Age

18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.Patients who underwent surgical treatment and had definite pathological results; 2.Underwent gynecological ultrasound examination before surgery;

Exclusion criteria

Exclusion criteria: 1.Insufficient ultrasound image documentation or suboptimal image quality; 2.The specific pathologic type is indeterminate. 3.Non-adnexal primary malignant tumor;

Design outcomes

Primary

Measure	Time frame
Area Under the Curve;	—

Secondary

Measure	Time frame
Positive Likelihood Ratio/Negative Likelihood Ratio/Diagnostic Odds Ratio;Calibration;Brier Score (BS);Sensitivity/Specificity/Negative Predictive Value/Positive Predictive Value;	—

Countries

China

Contacts

Public ContactChen hui

Ruijin Hospital, Shanghai Jiao Tong University School of Medicine

ch11516@rjh.com.cn+86 180 1867 6996

Outcome results

None listed

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