在人工智能时代对角关闭疾病的评估:一篇综述
Zhi Da Soh1, Mingrui Tan2, Monisha Esther Nongpiur3
1Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, 169856, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, 21 Lower Kent Ridge Road, 119077, Singapore.
Progress in retinal and eye research
|November 5, 2023
概括
人工智能 (AI) 在检测和评估初级角度闭合疾病 (PACD) 中表现有前途. 深度学习模型的性能优于传统方法,但实际的部署需要进一步评估.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 主要闭角光眼 (PACG) 是一种被诊断不足,视力衰弱的疾病.
- 目前的PACG管理受到缺乏准确,可访问的临床评估工具的阻碍.
- 人工智能 (AI) 为改善PACG检测和监测提供了潜在的解决方案.
研究的目的:
- 审查人工智能的现状和潜力,特别是机器学习 (ML) 和深度学习 (DL),用于诊断和评估初级角度闭合疾病 (PACD).
- 突出AI算法在分类角度闭合机制和区分角度状态方面的性能.
- 为了确定人工智能工具在现实世界临床实践中的未来研发需求.
主要方法:
- 审查人工智能的最新进展,包括ML和DL算法,用于PACD检测和评估.
- 使用临床数据的传统ML方法与使用图像数据的DL方法的比较.
- 分析人工智能在分类疾病机制和量化眼睛参数方面的能力.
主要成果:
- ML算法有效地根据疾病机制对角度闭合进行分类.
- 在图像数据上训练的DL算法在检测PACD方面表现优异,与传统ML相比.
- DL模型准确地区分开放,狭窄和闭合的角度,并自动进行定量测量.
结论:
- 人工智能,特别是DL,显示出改善PACD的检测,评估和监测的巨大潜力.
- 需要进一步的研究来验证人工智能工具在现实世界的设置和解决部署挑战.
- 考虑到临床,经济,社会和政策因素对于人工智能在PACD管理中的成功整合至关重要.
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