CompletedNCT07581925

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

Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University

Trial Details

Condition	Ophthalmology, Artificial Intelligence (AI), Hepatobiliary Diseases, Systemic Diseases
Intervention	Systemic diseases such as Hepatobiliary Disorders
Status	Completed
Participants	775
Est. Completion	30 July 2024
Last Updated	14 May 2026

Primary Outcome

area under the receiver operating characteristic curve of the deep learning system

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: * The quality of ocular images should clinical acceptable. * Complete clinical information such as baseline demographic characteristics, the history of systematic diseases and so on. Exclusion Criteria: * Individuals diagnosed with severe eye diseases or acute systematic diseases. * Incompatible with ocular examinations.

Trial Sites

Countries

China

View Registry Entry

Related Analysis

Completed Oculomics Study Demonstrates AI Detection of Hepatobiliary Disease Through Retinal Imaging — Implications for Early Screening

Completed Chinese study demonstrates AI analysis of retinal images can detect hepatobiliary diseases with high accuracy. Research validates oculomics approach for non-invasive systemic disease screening through routine eye examinations.

Read full article →

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