AUCs (95%CIs) from ROC curves for classifying tumor presence status based on tumor presence confidence scores given by group and reader for all tumors (n = 107).
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https://figshare.com/articles/dataset/_AUCs_95_CIs_from_ROC_curves_for_classifying_tumor_presence_status_based_on_tumor_presence_confidence_scores_given_by_group_and_reader_for_all_tumors_n_107_/1534994
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* Comparisons between interpreters: ACPPD-Gd, p = 0.04; gadobutrol, p = 0.003; non-contrast, p = 0.0003.
AUCs (95%CIs) from ROC curves for classifying tumor presence status based on tumor presence confidence scores given by group and reader for all tumors (n = 107).
阅片者间的对比:ACPPD-Gd,p=0.04;钆布醇(gadobutrol),p=0.003;无对比增强组,p=0.0003。针对全部107例肿瘤,基于各分组与阅片者给出的肿瘤存在置信度评分,通过受试者工作特征(Receiver Operating Characteristic, ROC)曲线计算得到的肿瘤存在与否分类的曲线下面积(Area Under Curve, AUC)与95%置信区间(95% Confidence Intervals, 95%CIs)。
创建时间:
2015-09-03



