Screening and Identifying Hepatobiliary Diseases Via Deep Learning Using Ocular Images

Sun Yat-sen University

Status: Completed

Conditions: Artificial Intelligence; Ophthalmology; Hepatobiliary Disease

Treatments: Diagnostic Test: Hepatobiliary Disorders

Study type: Observational

Funder types: Other

Identifiers

NCT04213183

AEHD-2019

Details and patient eligibility

About

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 conducted a pioneer work to explore the association between the eye and liver via deep learning, to develop and evaluate different deep learning models to predict the hepatobiliary disease by using ocular images.

Enrollment: 1,789 patients

Sex: All

Volunteers: Accepts Healthy Volunteers

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.

Trial design

1,789 participants in 5 patient groups

development dataset 01

Description:

Slit-lamp and retinal fundus images collected from Department of Hepatobiliary Surgery of the Third Affiliated Hospital of Sun Yat-sen University.

Treatment:

Diagnostic Test: Hepatobiliary Disorders

development dataset 02

Description:

Slit-lamp and retinal fundus images collected from Affiliated Huadu Hospital of Southern Medical University.

Treatment:

Diagnostic Test: Hepatobiliary Disorders

development dataset 03

Description:

Slit-lamp and retinal fundus images collected from Nantian Medical Centre of Aikang Health Care.

Treatment:

Diagnostic Test: Hepatobiliary Disorders

test dataset 01

Description:

Slit-lamp and retinal fundus images collected from Department of Infectious Diseases, Third Affiliated Hospital of Sun Yat-sen University.

Treatment:

Diagnostic Test: Hepatobiliary Disorders

test dataset 02

Description:

Slit-lamp and retinal fundus images collected from Huanshidong Medical Centre of Aikang Health Care.

Treatment:

Diagnostic Test: Hepatobiliary Disorders