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COMPLETEDNCT04213183

Screening and Identifying Hepatobiliary Diseases Via Deep Learning Using Ocular Images

Artificial Intelligence may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in individuals with hepatobiliary disorders. We con...

Lead sponsor: Sun Yat-sen University•1 locations•View source on ClinicalTrials.gov

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Sponsors

Lead Sponsor

Sun Yat-sen University

Collaborators

Third Affiliated Hospital, Sun Yat-Sen University
Affiliated Huadu Hospital of Southern Medical University
Aikang Health Care

Age

All ages

Sex

ALL

Healthy Volunteers

Yes

Inclusion Criteria

•The quality of fundus and slit-lamp images should clinical acceptable.
•More than 90% of the fundus image area including four main regions (optic disk, macular, upper and lower retinal vessel archs) are easy to read and discriminate.
•More than 90% of the slit-lamp image area including three main regions (sclera, pupil, and lens) are easy to read and discriminate.

Exclusion Criteria

•Images with light leakage (\>10% of the area), spots from lens flares or stains, and overexposure were excluded from further analysis.

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Data from ClinicalTrials.govLast updated on ClinicalTrials.gov: August 18, 2020Terms

Trial snapshot

StatusCOMPLETED

Phase—

Enrollment1,789

Start dateDec 2018

Last updatedAug 18, 2020

Condition

Ophthalmology Artificial Intelligence Hepatobiliary Disease

Locations shown

Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity

Guangzhou, Guangdong

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Data Source & Attribution

This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.

ClinicalTrials.gov last update: August 18, 2020Data synced to Clareo: May 25, 2026

Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.

Neither the United States Government nor Clareo Health make any warranties regarding the data. Check ClinicalTrials.gov frequently for updates.

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