Machine-learning-derived predictive score for early estimation of COVID-19 mortality risk in hospitalized patients.

ABSTRACT: The clinical course of COVID-19 is highly variable. It is therefore essential to predict as early and accurately as possible the severity level of the disease in a COVID-19 patient who is admitted to the hospital. This means identifying the contributing factors of mortality and developing an easy-to-use score that could enable a fast assessment of the mortality risk using only information recorded at the hospitalization. A large database of adult patients with a confirmed diagnosis of COVID-19 (n = 15,628; with 2,846 deceased) admitted to Spanish hospitals between December 2019 and July 2020 was analyzed. By means of multiple machine learning algorithms, we developed models that could accurately predict their mortality. We used the information about classifiers' performance metrics and abo

SUBMITTER: Gonzalez-Cebrian A 

PROVIDER: S-EPMC9499271 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature