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Detection of Jaundice From Ocular Images Via Deep Learning

NCT05682105 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1633

Last updated 2023-01-12

No results posted yet for this study

Summary

Our study presents a detection model predicting a diagnosis of jaundice (clinical jaundice and occult jaundice) trained on prospective cohort data from slit-lamp photos and smartphone photos, demonstrating the model's validity and assisting clinical workers in identifying patient underlying hepatobiliary diseases.

Conditions

  • Ophthalmology
  • Artificial Intelligence
  • Hepatobiliary Disease

Sponsors & Collaborators

  • Third Affiliated Hospital, Sun Yat-Sen University

    collaborator OTHER

  • Affiliated Huadu Hospital of Southern Medical University

    collaborator UNKNOWN

  • Aikang Health Care

    collaborator UNKNOWN

  • Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2018-12-01
Primary Completion
2022-10-30
Completion
2023-06-30

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 NCT05682105 on ClinicalTrials.gov