Deep learning system for analyzing eye diseases
Explainable Multimodal Deep Neural Networks for Identifying Ocular Fundus Diseases and Report Generation
This study is testing a new computer system that looks at eye images to help doctors diagnose eye diseases more accurately and quickly.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 15000 (estimated) |
| Sex | All |
| Sponsor | Sun Yat-sen University Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Trial ID | NCT05622565 on ClinicalTrials.gov |
What this trial studies
This project aims to develop a deep learning system that analyzes various ocular fundus images to diagnose and generate reports for ocular diseases. Utilizing multiple imaging techniques such as Color Fundus Photography, Optical Coherence Tomography, and Fluorescein Fundus Angiography, the system will provide comprehensive insights into the health of the retina and choroid. The goal is to enhance the accuracy and efficiency of ocular disease diagnosis, addressing the shortage of specialists in this field. Multi-center data verification will ensure the robustness of the findings.
Who should consider this trial
Good fit: Ideal candidates for this study are individuals undergoing multimodal ocular fundus examinations with clinically acceptable image quality.
Not a fit: Patients with ocular fundus images that are of poor quality or missing key information may not benefit from this study.
Why it matters
Potential benefit: If successful, this system could significantly improve the diagnosis and management of ocular fundus diseases, leading to better patient outcomes.
How similar studies have performed: Other studies utilizing AI for medical image analysis have shown promising results, indicating potential success for this approach.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * The quality of multimodal ocular fundus disease examination images and corresponding reports should be clinically acceptable. Exclusion Criteria: * Reports with key information missing. * Images with severe image resolution reductions, blur or artifacts were excluded from further analysis.
Where this trial is running
Guangzhou, Guangdong
- Zhognshan Ophthalmic Center, Sun Yat-sen University — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Principal investigator: Yingfeng Zheng, M.D. Ph.D — Zhongshan Ophthalmic Center, Sun Yat-sen Univerisity,Guangzhou, Guangdong, China, 510060
- Study coordinator: Yingfeng Zheng, M.D. Ph.D
- Email: zhyfeng@mail.sysu.edu.cn
- Phone: +8613922286455
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.