Comparing decision tree-based ensemble machine learning models for covid-19 death probability profiling

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dc.contributor.authorGonçalves, Carlos Pedro
dc.contributor.authorRouco, José
dc.contributor.institutionEscola de Ciências Económicas e das Organizações
dc.date.issued2021
dc.descriptionJournal of Vaccines & Vaccination
dc.description.abstractBackground: Age group, sex and underlying comorbidity or disease have been identified as major risk factors in COVID-19 severity and death risk. Aim: We compare the performance of major decision tree-based ensemble machine learning models on the task of COVID-19 death probability prediction, conditional on three risk factors: age group, sex and underlying comorbidity or disease, using the US Centers for Disease Control and Prevention (CDC)’s COVID-19 case surveillance dataset. Method: To evaluate the impact of the three risk factors on COVID-19 death probability, we extract and analyze the conditional probability profile produced by the best performing model. Result: The results show the presence of an exponential rise in death probability from COVID-19 with the age group, with males exhibiting a higher exponential growth rate than females, an effect that is stronger when an underlying comorbidity or disease is present, which also acts as an accelerator of COVID-19 death probability rise for both male and female subjects. These results are discussed in connection to healthcare and epidemiological concerns and in the degree to which they reinforce findings coming from other studies on COVID-19.en
dc.description.statusNon peer reviewed
dc.formatapplication/pdf
dc.identifier.citationGonçalves , C P & Rouco , J 2021 , ' Comparing decision tree-based ensemble machine learning models for covid-19 death probability profiling ' , Default journal .
dc.identifier.issn1646-3730
dc.language.isoeng
dc.publisherEdições Universitárias Lusófonas
dc.relation.ispartofDefault journal
dc.rightsopenAccess
dc.subjectMATEMÁTICA
dc.subjectAPRENDIZAGEM COMPUTACIONAL
dc.subjectCÁLCULO DE PROBABILIDADES
dc.subjectREGRESSÕES LOGÍSTICAS
dc.subjectCOVID-19
dc.subjectMATHEMATICS
dc.subjectMACHINE LEARNING
dc.subjectPROBABILITY CALCULUS
dc.subjectLOGISTIC REGRESSIONS
dc.subjectCOVID-19
dc.titleComparing decision tree-based ensemble machine learning models for covid-19 death probability profilingen

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