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The potential application of artificial intelligence for diagnosis and management of glaucoma in adults

机译:人工智能对成人青光眼诊断和管理的潜在应用

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Background: Glaucoma is the most frequent cause of irreversible blindness worldwide. There is no cure, but early detection and treatment can slow the progression and prevent loss of vision. It has been suggested that artificial intelligence (AI) has potential application for detection and management of glaucoma. Sources of data: This literature review is based on articles published in peer-reviewed journals. Areas of agreement: There have been significant advances in both AI and imaging techniques that are able to identify the early signs of glaucomatous damage. Machine and deep learning algorithms show capabilities equivalent to human experts, if not superior. Areas of controversy: Concerns that the increased reliance on AI may lead to deskilling of clinicians. Growing points: AI has potential to be used in virtual review clinics, telemedicine and as a training tool for junior doctors. Unsupervised AI techniques offer the potential of uncovering currently unrecognized patterns of disease. If this promise is fulfilled, AI may then be of use in challenging cases or where a second opinion is desirable. Areas timely for developing research: There is a need to determine the external validity of deep learning algorithms and to better understand how the 'black box' paradigm reaches results.
机译:背景:青光眼是全球不可逆失明的最常见原因。没有治愈,但早期的检测和治疗可以减缓进展和防止视力丧失。有人提出,人工智能(AI)具有潜在的缺乏症和管理青光眼的应用。数据来源:本文文献综述是基于在同行评审期刊上发表的文章。协议领域:AI和成像技术都有显着的进展,能够识别青光眼损伤的早期迹象。机器和深度学习算法显示相当于人类专家的能力,如果不是优越的话。争议地区:担心增加对AI的依赖可能导致临床医生的桌面。增长点:AI有可能用于虚拟审查诊所,远程医疗和初级医生的培训工具。无监督的AI技术提供了揭示目前无法识别的疾病模式的潜力。如果履行了这一承诺,则AI则可以在挑战性情况下使用,或者第二意见是可取的。及时开发研究的领域:需要确定深度学习算法的外部有效性,并更好地了解“黑匣子的范例”如何达到结果。

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