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The aim herein is to establish an open\u2010access web\u2010based prediction system, which estimates CDI patients\u2019 mortality and recurrence outcomes and explains machine learning prediction with patients\u2019 characteristics. Prognostic models are developed using four various types of machine learning algorithms and the statistical logistics regression model utilizing over 15\u2009000 CDI patients from 41 hospitals in Hong Kong. The boosting\u2010based machine learning algorithm gradient boosting machine (GBM) (Mortality AUC: 0.7878; Recurrence AUC: 0.7076) outperforms statistical models (Mortality AUC: 0.7573; Recurrence AUC: 0.6927) and other machine learning algorithms. As the difficulty to interpret complex machine learning results limits their use in the medical area, Shapley additive explanations (SHAP) are adapted to identify which features are crucial to the machine learning models and associate them with clinical findings. SHAP analysis shows that older age, reduced albumin levels, higher creatinine levels, and higher white blood cell count are the most highly associated mortality features, which is consistent with existing clinical findings. The open\u2010access prediction system for clinicians to assess and interpret the risk factors of CDI patients is now available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/www.cdiml.care\/\">https:\/\/www.cdiml.care\/<\/jats:ext-link>.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202000188","type":"journal-article","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T04:17:02Z","timestamp":1605500222000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Development of an Open\u2010Access and Explainable Machine Learning Prediction System to Assess the Mortality and Recurrence Risk Factors of <i>Clostridioides Difficile<\/i> Infection Patients"],"prefix":"10.1002","volume":"3","author":[{"given":"Yui-Lun","family":"Ng","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering Faculty of Engineering The University of Hong Kong  7\/F, Haking Wong Building Pokfulam Road Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michelle C. 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