Ophthalmology is undergoing a profound transformation driven by artificial intelligence (AI), represented by deep learning technologies.As the frontier of AI advancement, large language models (LLMs) demonstrate substantial potential in processing massive unstructured medical text and assisting with complex clinical reasoning.The DeepSeek series models, as exemplary advanced LLMs, provide novel opportunities for ophthalmic clinical practice, scientific research, and administrative management through their exceptional reasoning capabilities, remarkable cost-effectiveness, and open-source nature.Given research specifically targeting DeepSeek's ophthalmological applications remains nascent, this review systematically delineates its potential in diagnostic assistance, natural language processing, and functioning as the linguistic core for multimodal systems, which is achieved by precisely defining its LLM capabilities and benchmarking against validated applications of comparable advanced models.This article thoroughly discusses critical challenges including model " hallucinations", data governance, and regulatory approvals in clinical practice, aiming to provide early, rigorous academic guidance for this emerging interdisciplinary field and promote the healthy, standardized, and innovative advancement of DeepSeek technology in ophthalmology.

Ophthalmology is undergoing a profound transformation driven by artificial intelligence (AI), represented by deep learning technologies.As the frontier of AI advancement, large language models (LLMs) demonstrate substantial potential in processing massive unstructured medical text and assisting with complex clinical reasoning.The DeepSeek series models, as exemplary advanced LLMs, provide novel opportunities for ophthalmic clinical practice, scientific research, and administrative management through their exceptional reasoning capabilities, remarkable cost-effectiveness, and open-source nature.Given research specifically targeting DeepSeek's ophthalmological applications remains nascent, this review systematically delineates its potential in diagnostic assistance, natural language processing, and functioning as the linguistic core for multimodal systems, which is achieved by precisely defining its LLM capabilities and benchmarking against validated applications of comparable advanced models.This article thoroughly discusses critical challenges including model " hallucinations", data governance, and regulatory approvals in clinical practice, aiming to provide early, rigorous academic guidance for this emerging interdisciplinary field and promote the healthy, standardized, and innovative advancement of DeepSeek technology in ophthalmology.

AIM: To evaluate the changes in corneal epithelial thickness(CET)and corneal optical density(CD)after smart pulse technology(SPT)-assisted transepithelial photorefractive keratectomy(TPRK)and analyze their correlation.METHODS: The prospective study included 60 patients(120 eyes)with myopia and myopic astigmatism who underwent SPT-TPRK in the ophthalmology department at the First Affiliated Hospital of Xinxiang Medical University between February and August 2023. Changes in CET and CD were evaluated preoperatively and at 1 wk, 1 and 3 mo postoperatively.RESULTS: A total of 14 cases(28 eyes)were lost to follow-up, and 3 patients(6 eyes)with postoperative haze were excluded from this study, resulting in a final inclusion of 43 patients(86 eyes). At 1 wk after SPT-TPRK, CET had statistically significantly thickened compared to preoperative levels(P<0.05), particularly in the CET at 0-2 mm central corneal area(P<0.05). At 1 mo after SPT-TPRK, the CET at 0-2 mm area had statistically significantly decreased(P<0.05). At 3 mo after SPT-TPRK, the CET at 0-2 mm had essentially reached preoperative levels. Postoperative CD values increased, with a positive correlation between CET in the 0-2 mm area and CD in the whole 0-2 mm area(r=0.256, P<0.05), and a positive correlation between CET in the 2-5 mm area and CD in the anterior 2-6 mm area(r=0.319, P<0.05).CONCLUSION: Corneal epithelial remodeling takes 3 mo in areas within 2 mm of the central cornea; areas with thinner CET have faster postoperative corneal epithelial remodeling and greater thickening in the early postoperative period; CD increases in the early postoperative period compared to the preoperative value, and in some areas, there is a positive correlation between CET and CD value.