Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopia

Lim, Wee ShinWee ShinLimHo, Heng-YenHeng-YenHoHo, Heng-ChenHeng-ChenHoChen, Yan-WuYan-WuChenCHIH-KUO LEEChen, Pao-JuPao-JuChenLai, FeipeiFeipeiLaiJang, Jyh-Shing RogerJyh-Shing RogerJangMEI-LAN KO2023-04-122023-04-122022-11-241471-2342https://scholars.lib.ntu.edu.tw/handle/123456789/630121Glaucoma is one of the major causes of blindness; it is estimated that over 110 million people will be affected by glaucoma worldwide by 2040. Research on glaucoma detection using deep learning technology has been increasing, but the diagnosis of glaucoma in a large population with high incidence of myopia remains a challenge. This study aimed to provide a decision support system for the automatic detection of glaucoma using fundus images, which can be applied for general screening, especially in areas of high incidence of myopia.enDeep learningGlaucomaMultimodal learning modelOphthalmology[SDGs]SDG3Use of multimodal dataset in AI for detecting glaucoma based on fundus photographs assessed with OCT: focus group study on high prevalence of myopiajournal article10.1186/s12880-022-00933-z364345082-s2.0-85142505541WOS:000888737400003