The CT-based Deep Learning Model Predicts Complications in Partial Nephrectomy

NCT06876584 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1474

Last updated 2025-03-14

No results posted yet for this study

Summary

The investigators combine radiomics and deep learning to analyze the lesions more thoroughly, aiming for a more accurate prediction of complications in partial nephrectomy, and compare this approach with traditional models.

Conditions

  • Renal Cell Carcinoma (RCC)
  • Renal Cyst

Sponsors & Collaborators

  • Shanghai Zhongshan Hospital

    collaborator OTHER
  • Minhang Hospital, Fudan University

    collaborator UNKNOWN
  • Xuhui Central Hospital, Shanghai

    collaborator OTHER
  • Du Lingzhi

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-06-01
Primary Completion
2024-12-31
Completion
2025-02-28

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06876584 on ClinicalTrials.gov