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In Vivo Computer-aided Prediction of Polyp Histology on White Light Colonoscopy

NCT03775811 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 90

Last updated 2023-01-18

No results posted yet for this study

Summary

Our group, prior to the present study, developed a handcrafted predictive model based on the extraction of surface patterns (textons) with a diagnostic accuracy of over 90%24. This method was validated in a small dataset containing only high-quality images.

Artificial intelligence is expected to improve the accuracy of colorectal polyp optical diagnosis. We propose a hybrid approach combining a Deep learning (DL) system with polyp features indicated by clinicians (HybridAI). A pilot in vivo experiment will carried out.

Conditions

  • Colonoscopy
  • Histology
  • Computer-aided Diagnosis
  • Artificial Intelligence
  • Colorectal Polyp
  • Adenoma Colon Polyp
  • Hyperplastic Polyp

Interventions

OTHER

AUTOMATED POLYP CLASSIFICATION

COLONIC POLYP HISTOLOGY PREDICTION IN WHITE LIGHT IMAGES COMBINING ARTIFICIAL INTELLIGENCE AND CLINICAL INFORMATION

Sponsors & Collaborators

  • Instituto de Salud Carlos III

    collaborator OTHER_GOV

  • Hospital Clinic of Barcelona

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-01-01
Primary Completion
2019-03-31
Completion
2022-12-31

Countries

  • Spain

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 NCT03775811 on ClinicalTrials.gov