基于人工智能的早产儿视网膜病变远程医疗筛查评估。
Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity.
机构信息
Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Portland.
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston.
出版信息
J AAPOS. 2020 Jun;24(3):160-162. doi: 10.1016/j.jaapos.2020.01.014. Epub 2020 Apr 11.
Abstract
Retrospective evaluation of a deep learning-derived retinopathy of prematurity (ROP) vascular severity score in an operational ROP screening program demonstrated high diagnostic performance for detection of type 2 or worse ROP. To our knowledge, this is the first report in the literature that evaluated the use of artificial intelligence for ROP screening and represents a proof of concept. With further prospective validation, this technology might improve the accuracy, efficiency, and objectivity of diagnosis and facilitate earlier detection of disease progression in patients with potentially blinding ROP.
摘要
回顾性评估深度学习衍生的早产儿视网膜病变（ROP）血管严重程度评分在常规 ROP 筛查项目中的表现，该评分对 2 期及以上 ROP 的检出具有较高的诊断性能。据我们所知，这是文献中首次评估人工智能在 ROP 筛查中的应用，代表了一种概念验证。随着进一步的前瞻性验证，该技术可能会提高诊断的准确性、效率和客观性，并有助于更早地发现有潜在致盲风险的 ROP 患者的疾病进展。
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