Trials / Completed
CompletedNCT04213183
Screening and Identifying Hepatobiliary Diseases Via Deep Learning Using Ocular Images
- Status
- Completed
- Phase
- —
- Study type
- Observational
- Enrollment
- 1,789 (actual)
- Sponsor
- Sun Yat-sen University · Academic / Other
- Sex
- All
- Age
- —
- Healthy volunteers
- Accepted
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.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| 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. |
Timeline
- Start date
- 2018-12-01
- Primary completion
- 2020-01-31
- Completion
- 2020-01-31
- First posted
- 2019-12-30
- Last updated
- 2020-08-18
Locations
1 site across 1 country: China
Source: ClinicalTrials.gov record NCT04213183. Inclusion in this directory is not an endorsement.