… We hypothesized that learning that COVID-19 mortality risks were higher than initially
thought could nudge people to act more prosocially or conversely that learning that they were …

… factors, we took an inductive approach for identifying potential risk factors for COVID-19
mortality. The feature selection began with a computational algorithm that MSMR 11,12 . We …

… In conclusion, our study included a cohort of COVID-19 patients with a mortality rate of
17.1%. Several risk factors were identified considering both clinical and statistical significance. …

… mortality in our cohort of patients admitted with covid-19 and is commonly included in other
existing covid-19 … Discriminatory performance of existing covid-19 scores applied to our …

… at high risk of severe illness or mortality is … COVID-19 to help predict disease severity and
mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk …

… To evaluate the markers of imminent mortality risk, we assessed the contribution of each
patient parameter to decisions of the algorithm. Features were ranked by Multi-tree XGBoost …

… To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus
disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This …

… This study analyzed 331,298 positive cases of COVID-19 to assess the risk factors associated
with mortality. Clinical characteristics of patients who survived and who did not survive are …

… patients and perform early interventions for high-risk patients. The present study aimed to …
mortality of COVID-19 patients and elucidate the risk factors of mortality in COVID-19 patients. …

… This study applies Deep Learning techniques for mortality prediction of COVID-19 patients.
Two datasets with clinical information were used. They included 2,307 and 3,870 COVID-19 …