早产儿视网膜病变严重程度评分

Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, S. Ostmo, J. P. Campbell, M. Chiang, Jennifer G. Dy, Deniz Erdoğmuş, Stratis Ioannidis
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引用次数: 10

摘要

早产儿视网膜病变(ROP)是全球儿童失明的主要原因。自动化ROP检测系统可以显著提高儿童接受正确诊断和治疗的机会。我们提出了一种以自动化方式产生连续严重性评分的方法,从(a)诊断类别标签和(b)比较结果进行回归。我们的生成模型结合了这两个来源,并成功地解决了诊断结果的内在变异性。特别是,我们的方法在广泛的指标(包括AUC、精度和召回率)上对诊断和比较结果都表现出出色的预测性能。
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A Severity Score for Retinopathy of Prematurity
Retinopathy of Prematurity (ROP) is a leading cause for childhood blindness worldwide. An automated ROP detection system could significantly improve the chance of a child receiving proper diagnosis and treatment. We propose a means of producing a continuous severity score in an automated fashion, regressed from both (a) diagnostic class labels as well as (b) comparison outcomes. Our generative model combines the two sources, and successfully addresses inherent variability in diagnostic outcomes. In particular, our method exhibits an excellent predictive performance of both diagnostic and comparison outcomes over a broad array of metrics, including AUC, precision, and recall.
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