Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy.

Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy.
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人工智能推动糖尿病视网膜病变的诊断和筛查。

DOI:
10.3389/fendo.2022.946915
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发表时间:
2022
影响因子:
5.2
通讯作者:
--
中科院分区:
医学2区
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--
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深度学习演变成一种新形式的机器学习技术,被归类为人工智能(AI),它具有大规模医疗筛查的巨大潜力,并可以为个体患者确定最合适的特定治疗。诊断技术的最新发展促进了代谢和内分泌学对视网膜疾病和眼部疾病的研究。在全球范围内,糖尿病视网膜病变(DR)被认为是视力丧失的主要原因。深度学习系统在从数字眼底照片或光学相干断层扫描检测DR方面是有效和准确的。因此,使用人工智能技术,可以开发出高准确性和高效率的系统,用于早期诊断和筛查DR,而无需仅在特殊诊所才能获得的资源。深度学习能够实现具有高度特异性和灵敏度的早期诊断,从而基于最低程度的手工特征做出决策,为个性化DR进展实时监测和及时的眼科或内分泌治疗铺平道路。本文将讨论最前沿的人工智能算法、DR分期分级和特征分割的自动检测系统、DR结局和治疗的预测以及人工智能揭示的其他系统性疾病的眼科适应症。
Deep learning evolves into a new form of machine learning technology that is classified under artificial intelligence (AI), which has substantial potential for large-scale healthcare screening and may allow the determination of the most appropriate specific treatment for individual patients. Recent developments in diagnostic technologies facilitated studies on retinal conditions and ocular disease in metabolism and endocrinology. Globally, diabetic retinopathy (DR) is regarded as a major cause of vision loss. Deep learning systems are effective and accurate in the detection of DR from digital fundus photographs or optical coherence tomography. Thus, using AI techniques, systems with high accuracy and efficiency can be developed for diagnosing and screening DR at an early stage and without the resources that are only accessible in special clinics. Deep learning enables early diagnosis with high specificity and sensitivity, which makes decisions based on minimally handcrafted features paving the way for personalized DR progression real-time monitoring and in-time ophthalmic or endocrine therapies. This review will discuss cutting-edge AI algorithms, the automated detecting systems of DR stage grading and feature segmentation, the prediction of DR outcomes and therapeutics, and the ophthalmic indications of other systemic diseases revealed by AI.
DOI: 10.1001/jamaophthalmol.2020.3256
发表时间: 2020-10-01
期刊: JAMA ophthalmology
影响因子: 8.1
作者:
Hunt MS;Kihara Y;Lee AY
通讯作者: Lee AY