Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS (Deemed to be University), Mumbai, India.
Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS (Deemed to be University), Mumbai, India.
Comput Med Imaging Graph. 2021 Jan;87:101818. doi: 10.1016/j.compmedimag.2020.101818. Epub 2020 Nov 24.
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma can prevent irreversible vision loss and glaucomatous structural damages to the eye. However, greater chances of misdiagnosis by the currently used conventional methods for diagnosis open up ways for more advanced techniques like the use of artificial intelligence (AI). Artificial intelligence coupled with optical coherence tomography imaging creates an algorithm that can be effectively used to make a model of complex data for detection as well as diagnosis of glaucoma. The present review is an attempt to provide state-of-the-art information on various AI techniques used in the diagnosis and assessment of glaucoma. The second part of the review is focused on understanding how the AI along with machine learning (ML) can be potentially used to be subjected for software as a medical device (SaMD) in precise diagnosis or early detection of disease conditions.
青光眼是一组以眼内压升高、视神经病变和视野缺损模式为特征的眼部疾病。早期、正确地诊断青光眼可以预防不可逆转的视力丧失和青光眼对眼睛的结构性损害。然而，目前用于诊断的常规方法误诊的可能性更大，这为人工智能（AI）等更先进的技术开辟了道路。人工智能与光学相干断层扫描成像相结合，创建了一个算法，可以有效地用于对复杂数据进行建模，以进行青光眼的检测和诊断。本综述旨在提供有关在青光眼的诊断和评估中使用的各种 AI 技术的最新信息。综述的第二部分重点讨论了如何将人工智能与机器学习（ML）结合起来，以便在精确诊断或早期发现疾病状况时，将其作为一种医疗设备软件（SaMD）进行应用。
