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Development and validation of an artificial intelligence diagnostic model for urothelial carcinoma based on urine cytology

Development and validation of an artificial intelligence diagnostic model for urothelial carcinoma based on urine cytology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200062163
Enrollment
Unknown
Registered
2022-07-26
Start date
2022-08-01
Completion date
Unknown
Last updated
2023-04-03

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

Conditions

urothelium carcinoma

Interventions

Gold Standard:Postoperative histopathological diagnosis and follow-up results
Index test:artificial&#32
intelligence&#32
diagnosis

Sponsors

Sun Yat-sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.Patients who underwent urine exfoliation cytology, 2.Complete clinical and pathological data.

Exclusion criteria

Exclusion criteria: 1.Poor slide quality, fading and dissolution of cells, 2.Incomplete clinical and pathological data.

Design outcomes

Primary

MeasureTime frame
accuracy;—

Countries

China

Contacts

Public ContactLin Tianxin
lintx@mail.sysu.edu.cn+86 13724008338

Outcome results

None listed

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