Explainable deep learning self-supervised vision transformer for fundus-based myopia classification

Eirini Maliagkani

doi:10.1111/aos.70205

2026-09-19

Eirini Maliagkani *

Christos Tsoutsas

Nikolaos Papageorgiou

Ioannis D. Apostolopoulos

Nikolaos Papandrianos

Ilias Georgalas

Elpiniki Papageorgiou

DOI：10.1111/aos.70205

原文链接

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摘要

En 中文

为开发并验证一种用于自动化三分类（正常、高度近视（HM）、病理性近视（PM））的自监督视觉Transformer（ViT）模型，该模型基于彩色眼底照片，并具有解剖学上忠实可解释性。

Keyword:

deep learning

explainable artificial intelligence

fundus photography

high myopia

pathologic myopia

vision transformer

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Acta Ophthalmologica

IF:

2.8

论文数:

1.1W

被引数:

1.1W

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