Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients - researchr publication authors

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Michael Netzer, Werner O. Hackl, Michael Schaller, Lisa Alber, Josef Marksteiner, Elske Ammenwerth. Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients. In Schreier Günter, Hayn Dieter, Eggerth Alphons, editors, dHealth 2020 - Biomedical Informatics for Health and Care - Proceedings of the 14th Health Informatics Meets Digital Health Conference, Vienna, Austria, 19-20 May 2020. Volume 271 of Studies in Health Technology and Informatics, pages 121-128, IOS Press, 2020. [doi]

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