Supplementary Table S1-S3 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group

Supplemental Table S1. Whole slide image tissue segmentation statistics by an expert pathologist and probability prediction using a trained convolutional neural network. Supplemental Table S2. Clinical and molecular characteristics of FN-RMS samples used for training models for mutation prediction. Yellow boxes indicate genes included in defining the RAS pathway. Supplemental Table S3. Clinical information with COG risk stratification of FN-RMS samples used for training a prognostication predictive CNN.

补充表S1：专业病理学家标注的全切片图像（Whole slide image）组织分割统计数据，以及经训练后的卷积神经网络（convolutional neural network）生成的概率预测结果。补充表S2：用于训练突变预测模型的纤维母细胞型横纹肌肉瘤（Fibroblastic Rhabdomyosarcoma, FN-RMS）样本的临床与分子特征；其中黄框标注了用于界定RAS通路的相关基因。补充表S3：用于训练预后预测卷积神经网络的FN-RMS样本的临床信息，包含儿童肿瘤协作组（Children's Oncology Group, COG）风险分层结果。