Sorrentino Francesco Saverio, Gardini Lorenzo, Fontana Luigi, Musa Mutali, Gabai Andrea, Maniaci Antonino, Lavalle Salvatore, D'Esposito Fabiana, Russo Andrea, Longo Antonio, Surico Pier Luigi, Gagliano Caterina, Zeppieri Marco
Unit of Ophthalmology, Department of Surgical Sciences, Ospedale Maggiore, 40100 Bologna, Italy.
Ophthalmology Unit, Department of Surgical Sciences, Alma Mater Studiorum University of Bologna, IRCCS Azienda Ospedaliero-Universitaria Bologna, 40100 Bologna, Italy.
J Pers Med. 2024 Jun 26;14(7):690. doi: 10.3390/jpm14070690.
An increasing amount of people are globally affected by retinal diseases, such as diabetes, vascular occlusions, maculopathy, alterations of systemic circulation, and metabolic syndrome.
This review will discuss novel technologies in and potential approaches to the detection and diagnosis of retinal diseases with the support of cutting-edge machines and artificial intelligence (AI).
The demand for retinal diagnostic imaging exams has increased, but the number of eye physicians or technicians is too little to meet the request. Thus, algorithms based on AI have been used, representing valid support for early detection and helping doctors to give diagnoses and make differential diagnosis. AI helps patients living far from hub centers to have tests and quick initial diagnosis, allowing them not to waste time in movements and waiting time for medical reply.
Highly automated systems for screening, early diagnosis, grading and tailored therapy will facilitate the care of people, even in remote lands or countries.
A potential massive and extensive use of AI might optimize the automated detection of tiny retinal alterations, allowing eye doctors to perform their best clinical assistance and to set the best options for the treatment of retinal diseases.
全球越来越多的人受到视网膜疾病的影响，如糖尿病、血管阻塞、黄斑病变、全身循环改变和代谢综合征。
本综述将探讨在前沿机器和人工智能（AI）支持下，视网膜疾病检测与诊断的新技术及潜在方法。
视网膜诊断成像检查的需求不断增加，但眼科医生或技术人员数量过少，无法满足需求。因此，基于AI的算法被采用，为早期检测提供了有效支持，并帮助医生进行诊断和鉴别诊断。AI帮助居住在远离中心枢纽地区的患者进行检查和快速初步诊断，使他们无需在往返途中浪费时间以及等待医疗回复。
高度自动化的筛查、早期诊断、分级和个性化治疗系统将有助于为人们提供医疗服务，即使是在偏远地区或国家。
AI的潜在大规模广泛应用可能会优化对微小视网膜病变的自动检测，使眼科医生能够提供最佳临床援助，并为视网膜疾病治疗设定最佳方案。
