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Application of Machine Learning Models to Reduce Need for Diagnostic EUS or MRCP in Patients With Intermediate Likelihood of Choledocholithiasis

NCT06066372 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2026-01-06

No results posted yet for this study

Summary

Machine learning predictive model can help in stratifying heterogenous intermediate likelihood group to reduce need for EUS or MRCP in selected subgroup of patients.

Conditions

  • Choledocholithiasis

Sponsors & Collaborators

  • Asian Institute of Gastroenterology, India

    lead OTHER

Principal Investigators

  • Mohan Ramchandani, MD · Asian Institute of Gastroenterology

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-10-01
Primary Completion
2026-06-30
Completion
2026-10-30

Countries

  • India

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 NCT06066372 on ClinicalTrials.gov