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Development and validation of a prognostic risk score system for COVID-19 inpatients: A multi-center retrospective study in China

Python 100.00%

risk_score_covid_19's Introduction

类/函数 与论文的对应关系

EDA

  • Model: 同济数据集训练,金银潭数据集验证,输出 StandardScaler 和 LR 参数

generate_score_form

  • score_form: 生成打分表,函数中的 w 变量为等效权重,对应论文中的死亡概率公式;打印出的结果对应论文最后打分表部分

svc_score

  • LR_model: 实现 StandardScaler 和 LR,效果与 EDA 中的相同
  • show_confusion_matrix: 画混淆矩阵
  • compute_auc_all: 计算每个时间段的 AUC
  • plot_auc_time: 绘制不同时间段的 AUC,对应着论文中图1、S3、S6
  • get_survival_rate: 计算不同时间点的生存率,用于画km图
  • plot_Kaplan_Meier: 绘制K-M图
  • plot_svc_km: 绘制 LR 模型在给定测试数据集上的KM曲线,对应着论文中图2、S2、S5;还会输出一些比例,这些数据散落在文章中。
  • CRB_65、CURB_65、qSOFA: 计算相关医学指标
  • preprocess_tongji_data: 预处理统计数据
  • preprocess_comparison_data: 预处理得到用于比较不同打分方法的数据集
  • roc_comparison: 对比 LR 模型和其他传统打分算法的 ROC 曲线,对应论文中图3,图中的 AUC 数值散落在论文中
  • jyt_test: 针对金银潭测试集,调用上述相关功能函数,产生图片和数据
  • sz_test: 针对深圳测试集,调用上述相关功能函数,产生图片和数据

utils

通用函数

risk_score_covid_19's People

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