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An interpretable AI model integrating multi-scale data to quantify the recurrence risk of bladder cancer

An interpretable AI model integrating multi-scale data to quantify the recurrence risk of bladder cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104096
Enrollment
Unknown
Registered
2025-06-11
Start date
2025-07-01
Completion date
Unknown
Last updated
2025-06-16

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

Conditions

Bladder Cancer

Interventions

Sponsors

The Affiliated Hospital of Qingdao University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Bladder cancer confirmed by surgery; 2.Pelvic contrast-enhanced CT scan performed within 20 days before surgery; 3.Complete clinical and pathological data; 4.Clear HE-stained sections.

Exclusion criteria

Exclusion criteria: 1.Incomplete clinical data; 2.Poor quality of imaging or pathological images; 3.Unclear lesion margins; 4.Presence of other malignant tumors; 5.Received chemotherapy, radiotherapy, or immunotherapy before imaging examination.

Design outcomes

Primary

MeasureTime frame
Area Under the Receiver Operating Characteristic Curve ;Accuracy;

Secondary

MeasureTime frame
Sensitivity;Specificity;

Countries

China

Contacts

Public ContactHexiang Wang

The Affiliated Hospital of Qingdao University

17853299958@163.com+86 178 5329 9958

Outcome results

None listed

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