Using AI to improve diagnosis of eye diseases through various data sources
Official title: Natural language processing and medical imaging analysis for multi-modality computer assisted diagnosis of ophthalmic diseases
Funded at Yale University · NIH-11169455 · Data updated 2026-11-12
This study is working on using smart computer technology to help doctors better diagnose eye diseases by looking at different types of information, like medical images and patient histories, so that everyone can get the right care faster and prevent vision loss.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $249,000 |
| NIH project number | 4R00LM014024-03 |
| Project ID | NIH-11169455 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals experiencing symptoms related to ophthalmic diseases or those at risk for such conditions.
✕Less likely to help
Patients with non-ophthalmic conditions or those who do not have access to the required imaging and data resources may not benefit from this research.
What this research studies
This research aims to enhance the diagnosis of ophthalmic diseases by developing advanced artificial intelligence models that integrate multiple types of data, including medical images, clinical notes, and patient history. By utilizing natural language processing, the study seeks to extract valuable information from electronic health records to improve diagnostic accuracy and timeliness. The goal is to create a more comprehensive approach to diagnosing eye conditions, which is crucial for preventing vision loss. The research will also address the generalization of AI models across diverse patient demographics.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of eye diseases, ultimately improving patient outcomes and preserving vision.
How similar studies have gone: Other research has shown promise in using AI for medical diagnosis, particularly in ophthalmology, indicating that this approach has the potential for success.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Chen, Qingyu — Yale University
- Study coordinator: Chen, Qingyu
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.