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The Implementation of Computer-aided Detection in Training Improves the Quality of Future Colonoscopies

NCT06623331 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 6000

Last updated 2025-01-17

No results posted yet for this study

Summary

Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally.

Conditions

  • Quality Indicators, Health Care
  • Colonoscopy Diagnostic Techniques and Procedures
  • Artificial Intelligence (AI)

Interventions

OTHER

AI-enhanced endoscopy training

Endoscopists trained in AI-enhanced environment. Their quality indicators are measured after completing training, without additional AI enhancement.

OTHER

Conventional endoscopy training

Endoscopists trained conventionally

Sponsors & Collaborators

  • Jagiellonian University

    lead OTHER

Principal Investigators

  • Zofia Orzeszko, MD · Jagiellonian University

  • Miroslaw Szura, PhD, Prof. · Jagiellonian University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2024-01-31
Completion
2024-03-31

Countries

  • Poland

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 NCT06623331 on ClinicalTrials.gov