将智能手机技术与人工智能整合用于高级眼科护理:系统回顾

Kai Jin , Yingyu Li , Hongkang Wu , Yih Chung Tham , Victor Koh , Yitian Zhao , Ryo Kawasaki , Andrzej Grzybowski , Juan Ye
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引用次数: 0

摘要

背景智能手机技术与人工智能(AI)的融合彻底改变了眼科医疗的面貌,为眼科疾病的诊断、监测和管理提供了前所未有的机遇。正文 本综述包括 52 项研究,探讨了智能手机和人工智能在眼科领域的融合,描述了其对筛查方法、疾病检测、远程医疗计划和患者管理的共同影响。汇总研究结果表明,基于智能手机的人工智能筛查在各种眼科疾病(包括主要视网膜疾病、青光眼、白内障、儿童视力障碍和眼表疾病)的筛查中表现出色。此外,基于智能手机的成像模式与人工智能算法相结合,能够提供及时、高效和具有成本效益的眼部病变筛查。这种模式还能促进患者自我监测、远程患者监测,并提高眼科护理服务的可及性,尤其是在服务不足的地区。涉及数据隐私、算法验证、监管框架和信任问题的挑战仍有待解决。此外,对真实世界的实施情况进行评估也势在必行,而目前还缺乏真实世界的前瞻性研究。结论智能手机眼部成像与人工智能相结合,可实现更早的精确诊断、个性化治疗,并提高眼科护理服务的可及性。要想在负责任地利用这些创新技术的同时应对伦理和数据安全方面的挑战,合作是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integration of smartphone technology and artificial intelligence for advanced ophthalmic care: A systematic review

Background

The convergence of smartphone technology and artificial intelligence (AI) has revolutionized the landscape of ophthalmic care, offering unprecedented opportunities for diagnosis, monitoring, and management of ocular conditions. Nevertheless, there is a lack of systematic studies on discussing the integration of smartphone and AI in this field.

Main text

This review includes 52 studies, and explores the integration of smartphones and AI in ophthalmology, delineating its collective impact on screening methodologies, disease detection, telemedicine initiatives, and patient management. The collective findings from the curated studies indicate promising performance of the smartphone-based AI screening for various ocular diseases which encompass major retinal diseases, glaucoma, cataract, visual impairment in children and ocular surface diseases. Moreover, the utilization of smartphone-based imaging modalities, coupled with AI algorithms, is able to provide timely, efficient and cost-effective screening for ocular pathologies. This modality can also facilitate patient self-monitoring, remote patient monitoring and enhancing accessibility to eye care services, particularly in underserved regions. Challenges involving data privacy, algorithm validation, regulatory frameworks and issues of trust are still need to be addressed. Furthermore, evaluation on real-world implementation is imperative as well, and real-world prospective studies are currently lacking.

Conclusions

Smartphone ocular imaging merged with AI enables earlier, precise diagnoses, personalized treatments, and enhanced service accessibility in eye care. Collaboration is crucial to navigate ethical and data security challenges while responsibly leveraging these innovations, promising a potential revolution in care access and global eye health equity.

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CiteScore
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