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Detection of Systemic Diseases Such as Hepatobiliary Diseases From Ocular Images Via Deep Learning

NCT07581925 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 775

Last updated 2026-05-14

No results posted yet for this study

Summary

Oculomics is an emerging interdisciplinary field that deciphers multi-dimensional, high-throughput ocular data to predict, diagnose, and monitor systemic diseases and health span.In recent years, artificial Intelligence may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in individuals with systemic diseases. The investigators conducted a survey to explore the association between the eye and systemic diseases via deep learning, to develop and evaluate different deep learning models to predict the systemic diseases such as hepatobiliary disease by using ocular images.

Conditions

  • Ophthalmology
  • Artificial Intelligence (AI)
  • Hepatobiliary Diseases
  • Systemic Diseases

Interventions

DIAGNOSTIC_TEST

Systemic diseases such as Hepatobiliary Disorders

The training dataset was used to train the deep learning model, which was validated and tested by the other two datasets.

Sponsors & Collaborators

  • Third Affiliated Hospital, Sun Yat-Sen University

    collaborator OTHER

  • Aikang Health Care

    collaborator UNKNOWN

  • Zhongshan Ophthalmic Center, Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-04-10
Primary Completion
2024-07-30
Completion
2024-07-30

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 NCT07581925 on ClinicalTrials.gov