基于人工智能模型量化视网膜血管特征参数预测子痫前期的可行性研究

周天凡, 邵飞雪, 万盛, 周晨晨, 周思锦, 花晓琳

Feasibility study on quantifying retinal vascular features for predicting preeclampsia based on artificial intelligence models

ZHOU Tianfan, SHAO Feixue, WAN Sheng, ZHOU Chenchen, ZHOU Sijin, HUA Xiaolin

图2 不同模型分别预测PE、早发型PE和晚发型PE的ROC曲线分析 Note： Predictive performance for PE (A), early-onset PE (B) and late-onset PE (C). MF—maternal risk factors.

Fig 2 Analysis of ROC curves for predicting PE, early-onset PE and late-onset PE using different models