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A two-stage artificial intelligence system based on deep learning assists radiologists to detect and classify breast lesions using Contrast Enhanced Mammography

A two-stage artificial intelligence system based on deep learning assists radiologists to detect and classify breast lesions using Contrast Enhanced Mammography

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200065169
Enrollment
Unknown
Registered
2022-10-30
Start date
2022-11-02
Completion date
Unknown
Last updated
2023-05-15

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

Conditions

Breast cancer

Interventions

Gold Standard:pathological result
Index test:Draw ROC curve to evaluate model performance

Sponsors

Yantai Yuhuangding Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
25 Years to 72 Years

Inclusion criteria

Inclusion criteria: ?Patients with suspicious lesions after CEM examination. ?Patients would undergo surgery or fine needle aspiration biopsy. ?Complete medical records including demographic and clinical ?Clear image quality.

Exclusion criteria

Exclusion criteria: ?There is a history of prior chemoradiotherapy or malignancy. ?Incomplete clinical or pathological information. ?Poor image quality. ?Multiple, bilateral or non-mass lesions.

Design outcomes

Primary

MeasureTime frame
receiver operating characteristic curve;sensitivity;specificity;—

Countries

China

Contacts

Public ContactMao Ning

Yantai Yuhuangding Hospital

maoning@pku.edu.cn13105351972

Outcome results

None listed

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