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  • 标题:Explainable machine learning model for predicting spontaneous bacterial peritonitis in cirrhotic patients with ascites
  • 本地全文:下载
  • 作者:Yingying Hu ; Ruijia Chen ; Haibing Gao
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2021
  • 卷号:11
  • DOI:10.1038/s41598-021-00218-5
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Spontaneous bacterial peritonitis (SBP) is a life-threatening complication in patients with cirrhosis. We aimed to develop an explainable machine learning model to achieve the early prediction and outcome interpretation of SBP. We used CatBoost algorithm to construct MODEL-1 with 46 variables. After dimensionality reduction, we constructed MODEL-2. We calculated and compared the sensitivity and negative predictive value (NPV) of MODEL-1 and MODEL-2. Finally, we used the SHAP (SHapley Additive exPlanations) method to provide insights into the model’s outcome or prediction. MODEL-2 (AUROC: 0.822; 95% confidence interval [CI
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