This article is about identifying predictors associated with risk of death or admission to intensive care unit in internal medicine patients with sepsis and comparing the results of statistical models and machine learning algorithms. The study found that statistical models were better at predicting mortality and admission to intensive care unit than machine learning algorithms.
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The article includes the name of Mahdiyeh Jami, the postdoc in the Faculty of Mathematics of the Institute for Research in Fundamental Sciences (IPM), Tehran, Iran. Jami is a scientist and researcher focused on machine learning and modeling. She has been an active researcher in the field of artificial intelligence and its applications in health prediction and related fields. Mahdiyeh has also been a member of several international research projects and has published a number of books and journals. She has presented her research findings on many international conferences and seminars.
