Decision-tree and ensemble-based mortality risk models for hospitalized patients with COVID-19 by Yaroslav Vyklyuk, Svitlana Levytska, Denys Nevinskyi, Kateryna Hazdiuk, Miroslav Škoda, Stanislav Andrushko, Maryna Palii

“…Using the good-known parameters that are routinely embraced in clinical practice, we obtained new functional dependencies based on an accessible and understandable decision tree and ML ensemble of classifiers models that would allow the physician to determine the prognosis in a few minutes and, accordingly, to understand the need for treatment adjustment, transfer of the patient to the emergency department. The accuracy of the resulting ensemble of models fitted on actual hospital patient data was in the range of 0.88–0.91 for different metrics. …”
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