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Nuclear polymorphism grading in breast cancer based on artificial intelligence

Nuclear polymorphism grading in breast cancer based on artificial intelligence

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300076103
Enrollment
Unknown
Registered
2023-09-25
Start date
2023-10-01
Completion date
Unknown
Last updated
2023-10-03

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:This study uses pathological reports as the gold standard.

Sponsors

Beijing Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Diagnosis time: January 1, 2017 to December 31, 2022; 2. The diagnostic key words are "breast cancer" or "invasive breast cancer"; 3. The morphology meets the diagnostic criteria for breast cancer identified by two pathologists.

Exclusion criteria

Exclusion criteria: 1. The patient's age is less than 18 years old; 2. The cases received preoperative radiotherapy or chemotherapy that may affect the cancer cell morphology; 3. The proportion of cancer in the entire tissue is less than 30%, which may affect subsequent image analysis; 4. The case was histologically confirmed as mixed or special breast cancer that the nuclear polymorphism grading is not required in diagnosis; 5. The surgical specimen comes from the metastatic site rather than the primary site; 6. The clinical pathological information of the patient is incomplete.

Design outcomes

Primary

MeasureTime frame
True positive rate;True negative rate;False positive rate;False positive rate;Accuracy;Sensitivity ;Specificity ;

Secondary

MeasureTime frame
Dice coefficient;IoU;

Countries

China

Contacts

Public ContactJunjie Li

Beijing Hospital

li_pathol210128@163.com+86 10 8513 3886

Outcome results

None listed

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