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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04213183
Other study ID # AEHD-2019
Secondary ID
Status Completed
Phase
First received
Last updated
Start date December 1, 2018
Est. completion date January 31, 2020

Study information

Verified date August 2020
Source Sun Yat-sen University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational [Patient Registry]

Clinical Trial Summary

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.


Recruitment information / eligibility

Status Completed
Enrollment 1789
Est. completion date January 31, 2020
Est. primary completion date January 31, 2020
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group N/A and older
Eligibility 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.

Study Design


Intervention

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

Locations

Country Name City State
China Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity Guangzhou Guangdong

Sponsors (4)

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

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary area under the receiver operating characteristic curve of the deep learning system The investigators will calculate the area under the receiver operating characteristic curve of deep learning system and compare this index between deep learning system and human doctors baseline
Secondary sensitivity and specificity of the deep learning system The investigators will calculate the sensitivity and specifity of deep learning system and compare this index between deep learning system and human doctors baseline
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