| Title: | Exploring innovative risk indicators for early prediction of ocular diseases through AI-driven multimodal data analysis |
| Lead Institution: | Nanchang University |
| Principal investigator: |
Application 597582
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About
Ocular diseases have imposed a heavy burden on global health. Their prevalence continues to rise, and the conditions are complex, posing numerous challenges to effective treatment. One of the main obstacles in combating ocular diseases lies in the fact that their initial symptoms are often latent. In cases like glaucoma, macular degeneration, and diabetic retinopathy, the early signs are frequently inconspicuous and difficult to detect. As a result, by the time obvious symptoms appear, the optimal treatment window has usually been missed, leading to more severe visual impairment and a reduced possibility of successful intervention. This research endeavor is committed to tackling this critical challenge, with a specific focus on the early and precise prediction of ocular diseases. By harnessing the extensive dataset of the UK Biobank, which encompasses rich information on demographics, clinical details, and lifestyle factors, we aim to apply artificial intelligence (AI) -driven multimodal data analysis techniques to pinpoint reliable and predictive risk indicators. Firstly, we will investigate the influence of systemic diseases, such as diabetes and hypertension, on the onset, progression, and severity of various ocular diseases. Secondly, we aspire to elucidate the interplay between lifestyle choices, genetic factors, and their collective contribution to the development of ocular diseases. Finally, leveraging the identification of novel risk factors associated with different ocular diseases, we will employ machine learning algorithms to construct a predictive model. The successful completion of this research has the potential to improve the lives of millions of individuals at risk of ocular diseases. By providing a more accurate and timely diagnosis and treatment approach, we can strive towards achieving better visual health outcomes and enhancing the quality of life for patients worldwide.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 20438 | Phenotypic age acceleration and genetic risk synergistically increase age-related eye disease risk in the UK Biobank | Haoyu Yuan (+1) | 2026 | Scientific Reports |
Enabling scientific discoveries that improve human health