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Establishment of an accurate prediction model based on the pathological features and prognosis of artificial intelligence kidney tumor

Establishment of an accurate prediction model based on the pathological features and prognosis of artificial intelligence kidney tumor

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1900025090
Enrollment
Unknown
Registered
2019-08-10
Start date
2019-09-01
Completion date
Unknown
Last updated
2019-08-27

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

Conditions

renal tumor

Interventions

Gold Standard:Postoperative pathology
Index test:Artificial&#32
intelligence&#32
diagnostic&#32
system

Sponsors

Department of urology, The First Affiliated Hospital of Fujian Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Plain CT scan + enhancement of the kidney was performed in our hospital; 2. complete preoperative and postoperative clinicopathological data.

Exclusion criteria

Exclusion criteria: 1. preoperative CT plain scan + enhanced imaging data; 2. no surgical treatment; 3. previous history of kidney surgery or other tumors.

Design outcomes

Primary

MeasureTime frame
Pathological type of tumor;Tumor volume;Sarcomatoid changes of the tumor;Tumor necrosis ratio;Fuhrman grade of tumor;Age;Body Mass Index;Patient survival situation;—

Countries

China

Contacts

Public ContactChen Shaohao

The First Affiliated Hospital of Fujian Medical University

shaohao.chen@fjmu.edu.cn+86 15159858088

Outcome results

None listed

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