In recent years, with the help of artificial intelligence technology such as deep learning (DL), ophthalmic diagnosis and treatment technology has been continuously developed and improved. This article reviews the DL-assisted cataract screening and diagnosis, surgical navigation and risk prediction, intraocular lens function optimization and postoperative complications prediction, aiming to summarize the research progress of various DL models currently applied in the field of cataract diagnosis and treatment, and explore the challenges and future development direction of DL application in the whole process management of cataract.
Povidone-iodine, an indispensable broad-spectrum and low-resistance antimicrobial agent in ophthalmology, holds dual therapeutic value: it serves as a preoperative conjunctival sac disinfectant to effectively prevent postoperative endophthalmitis, and as adjuvant therapy for refractory infectious eye diseases that respond poorly to conventional treatments. This article systematically summarizes the progress of clinical research on povidone-iodine, focusing on in-depth discussions of core issues such as the mechanism by which it achieves sterilization through free iodine, the controversy over concentration and exposure time in practical applications, and ocular surface safety. The aim is to provide a solid scientific basis for the standardized clinical application and future research of povidone-iodine.
