Construction of a Predictive Model of Gangrenous Cholecystitis Based on Machine Learning

NCT06399081 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1006

Last updated 2024-05-03

No results posted yet for this study

Summary

Gangrenous cholecystitis is the most common complication of acute cholecystitis.

There is no research using machine learning models to construct predictive diagnostic models for gangrenous cholecystitis.

Conditions

  • Gangrenous Cholecystitis

Interventions

OTHER

Observational

Observational

Sponsors & Collaborators

  • National Natural Science Foundation of China

    collaborator OTHER_GOV
  • Dalian Medical University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-12-01
Primary Completion
2024-03-01
Completion
2024-03-02

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 NCT06399081 on ClinicalTrials.gov