1.Aim:
1.1. To investigate an artificial intelligence algorithm for glaucoma, myopia, and myopia combined with glaucoma (MG) based on medical images.
1.2. To explore the factors associated with glaucoma, myopia and MG, including patients’ genetic information, systemic diseases, and living environment.
2. Scientific rationale:
2.1 Significance of the research project
Glaucoma is a progressive and potentially blinding eye disease. Fundus photography and optical coherence tomography (OCT) are practical tests for early glaucoma screening. Myopia is a global public problem and can double the risk of glaucoma. The optic disc of myopic eyes may appear tilted or stretched on the fundus photograph, similar to glaucoma. In OCT, the retinal nerve fiber layers defect potentially leading to a misdiagnosis of glaucoma. Therefore, developing more effective screening approaches for myopia and glaucoma are valuable.
2.2 Research status
Besides the traditional fundus examinations, multimodal brain fMRI provides a new understanding of glaucoma and myopia. Further correlation analysis between the eye and brain function may help the differential diagnosis.
AI has been applied in detecting glaucoma and myopia, and the researchers have shown its application prospect. However, little progress has been made in differentiating myopia from glaucoma. Here we attempt to develop a medical image algorithm and explore the influencing factors for glaucoma and myopia based on AI.
3. Project duration
The project will last for 3 years
4. Public health impact
4.1. Considering a wide range of examinations, our AI algorithm for screening glaucoma, myopia, and MG could assist in precise diagnosis and efficient therapy.
4.2. Our study will establish a comprehensive model including genetic and environmental information. The research will provide new diagnostic ideas and early prevention.