| Autor: |
Tiago Pessoa Ferreira Lima, Gabrielle Ribeiro Sena, Camila Soares Neves, Suely Arruda Vidal, Jurema Telles Oliveira Lima, Maria Julia Gonçalves Mello, Flávia Augusta de Orange Lins da Fonseca e Silva |
| Jazyk: |
English<br />Portuguese |
| Předmět: |
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| Zdroj: |
Revista Brasileira de Saúde Materno Infantil |
| Druh dokumentu: |
article |
| ISSN: |
1806-9304 |
| DOI: |
10.1590/1806-9304202100s200007 |
| Popis: |
Abstract Objectives: train a Random Forest (RF) classifier to estimate death risk in elderly people (over 60 years old) diagnosed with COVID-19 in Pernambuco. A "feature" of this classifier, called feature importance, was used to identify the attributes (main risk factors) related to the outcome (cure or death) through gaining information. Methods: data from confirmed cases of COVID-19 was obtained between February 13 and June 19, 2020, in Pernambuco, Brazil. The K-fold Cross Validation algorithm (K=10) assessed RF performance and the importance of clinical features. Results: the RF algorithm correctly classified 78.33% of the elderly people, with AUC of 0.839. Advanced age was the factor representing the highest risk of death. The main comorbidity and symptom were cardiovascular disease and oxygen saturation ≤ 95%, respectively. Conclusion: this study applied the RF classifier to predict risk of death and identified the main clinical features related to this outcome in elderly people with COVID-19 in the state of Pernambuco. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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