眼科人工智能研究的相关问题

Issues related to artificial intelligence research in ophthalmology

目前人工智能(AI)在多种眼科疾病的诊断治疗中取得了日益广泛的应用,但依然存在很多问题。由于AI产品的准确性缺乏标准测试集、金标准以及公认的评价体系,难以对多项研究结果进行横向比较。而在图像生成领域,评价体系更存在较大空白。在临床应用中,眼科AI研究常与临床实际需求脱节,被寄予了过高的期望,且对临床数据的质量及数量均具有较高的要求,限制了AI研究成果转化。利用眼底影像对全身性疾病进行预测、识别是新晋的研究热点,但其研究结果缺乏可解释性,限制了临床医生的接受度。眼科AI研究也因缺乏完善的法律规定、监管机制,涉及患者隐私风险及数据安全,且存在因商业化加重医疗资源不公平性的风险,而饱受伦理争议。

At present,artificial intelligence(AI)has been widely used in the diagnosis and treatment of various ophthalmological diseases,but there are still many problems.Due to the lack of standardized test sets,gold standards,and recognized evaluation systems for the accuracy of AI products,it is difficult to compare the results of multiple studies.When it comes to the field of image generation,we hardly have an efficient approach to evaluating research results.In clinical practice,ophthalmological AI research is often out of touch with actual clinical needs.The requirements for the quality and quantity of clinical data put more burden on AI research,limiting the transformation of AI studies.The prediction of systemic diseases based on fundus images is making progressive advancement.However,the lack of interpretability of the research lower the acceptance.Ophthalmology AI research also suffer from ethical controversy due to unconstructed regulations and regulatory mechanisms,concerns on patients*privacy and data security,and the risk of aggravating the unfairness of medical resources.