Cataract is an important cause of blindness and visual impairment worldwide. At present, the only effective treatment method is surgery. The visual function of most patients can be significantly improved after surgery, but there are still 5-20% of patients whose visual function cannot be improved after surgery. Previous studies have found that the surgical complications and postoperative visual function of cataract patients are closely related to the condition of the fundus, but the current fundus camera cannot perform clear fundus imaging of cataract patients, and the existing potential visual inspections, such as retinal visual inspection, are also inaccurate. Predict postoperative visual acuity. Therefore, there is an urgent need for a reliable postoperative effect prediction system for cataract patients to provide reference for both ophthalmologists and patients.

This study intends to collect patient medical record information and traditional/ultra-wide fundus photos and other multi-modal data. Firstly, this study will use artificial intelligence technology to enhance fundus photos of cataract patients to obtain clearer fundus photos. Then this study will use both medical record information and traditional/ultra-wide fundus photographs to predict postoperative vision and visual function of cataract patients.

Inclusion Criteria:

• Candidates for cataract surgery (phacoemulsification and intraocular lens implantation) within a week.

Exclusion Criteria:

• Unwilling or unable to receive fundus photography

All candidates for cataract surgery (phacoemulsification and intraocular lens implantation) within a week.