Interpretable Machine Learning Models for Prognosis in Gastric Cancer Patients

NCT06548464 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 18000

Last updated 2024-08-12

No results posted yet for this study

Summary

This multicenter, retrospective cohort study aimed to develop and validate an explainable prediction model for prognosis after gastrectomy in patients with gastric cancer.

Conditions

  • Stomach Neoplasms
  • Gastrectomy
  • Machine Learning

Sponsors & Collaborators

  • Chang-Ming Huang, Prof.

    lead OTHER

Principal Investigators

  • Chang-Ming Huang, MD · Fujian Medical University Union Hospital

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-06-01
Primary Completion
2024-08-01
Completion
2024-08-06

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 NCT06548464 on ClinicalTrials.gov