Artificial intelligence and digital solutions for myopia.

IF 1 Q4 OPHTHALMOLOGY Taiwan Journal of Ophthalmology Pub Date : 2023-05-16 eCollection Date: 2023-04-01 DOI:10.4103/tjo.TJO-D-23-00032
Yong Li, Michelle Y T Yip, Daniel S W Ting, Marcus Ang
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Abstract

Myopia as an uncorrected visual impairment is recognized as a global public health issue with an increasing burden on health-care systems. Moreover, high myopia increases one's risk of developing pathologic myopia, which can lead to irreversible visual impairment. Thus, increased resources are needed for the early identification of complications, timely intervention to prevent myopia progression, and treatment of complications. Emerging artificial intelligence (AI) and digital technologies may have the potential to tackle these unmet needs through automated detection for screening and risk stratification, individualized prediction, and prognostication of myopia progression. AI applications in myopia for children and adults have been developed for the detection, diagnosis, and prediction of progression. Novel AI technologies, including multimodal AI, explainable AI, federated learning, automated machine learning, and blockchain, may further improve prediction performance, safety, accessibility, and also circumvent concerns of explainability. Digital technology advancements include digital therapeutics, self-monitoring devices, virtual reality or augmented reality technology, and wearable devices - which provide possible avenues for monitoring myopia progression and control. However, there are challenges in the implementation of these technologies, which include requirements for specific infrastructure and resources, demonstrating clinically acceptable performance and safety of data management. Nonetheless, this remains an evolving field with the potential to address the growing global burden of myopia.

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人工智能和数字近视解决方案。
近视作为一种未矫正的视力损伤,已被公认为是一个全球性的公共卫生问题,对医疗保健系统造成的负担越来越重。此外,高度近视会增加患病理性近视的风险,从而导致不可逆转的视力损伤。因此,需要增加资源来早期识别并发症,及时干预以防止近视发展,并治疗并发症。新兴的人工智能(AI)和数字技术有可能通过自动检测筛查和风险分层、个性化预测以及近视发展的预后来满足这些尚未得到满足的需求。针对儿童和成人近视的人工智能应用已经开发出来,用于检测、诊断和预测近视的发展。新的人工智能技术,包括多模态人工智能、可解释人工智能、联合学习、自动机器学习和区块链,可能会进一步提高预测性能、安全性和可及性,并规避对可解释性的担忧。数字技术的进步包括数字疗法、自我监测设备、虚拟现实或增强现实技术以及可穿戴设备--这些都为监测和控制近视的发展提供了可能的途径。然而,这些技术的实施也面临着挑战,其中包括对特定基础设施和资源的要求、证明临床上可接受的性能以及数据管理的安全性。尽管如此,这仍然是一个不断发展的领域,有可能解决全球日益沉重的近视负担。
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来源期刊
CiteScore
1.80
自引率
9.10%
发文量
68
审稿时长
19 weeks
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