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Ronaldo Costa Couto

Biographic Data

ID892333
NAMERonaldo Costa Couto
GIVEN NAMESRonaldo Costa
FAMILY NAMECouto
SIGNATURECOUTO R C
AFFILIATIONSFaculdade de Ciências Médicas de Minas Gerais
ORCID0000-0003-4907-6295
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS0
AUTHOR COUNT5
EDITOR COUNT0
FIRST PUBLICATION YEAR1989
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Development of a machine learning modelto estimate length of stay in coronaryartery bypass grafting

    Open Access•Ronaldo Costa Couto, Tânia Moreira Grillo Pedrosa et al.•ARTICLE•Revista de Saúde Pública•2024

    OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.METHODS: Three machine learning models (random forest, extreme gradient boosting and neural networks) and three traditional regression models (Poisson regression, linear regression, negative binomial regression) were trained in a dataset of 9,584 patient…

  • Covid-19 vaccination priorities defined on machine learning

    Open Access•Ronaldo Costa Couto, Tânia Moreira Grillo Pedrosa et al.•ARTICLE•Revista de Saúde Pública•2022

    OBJECTIVE: Defining priority vaccination groups is a critical factor to reduce mortality rates. METHODS: We sought to identify priority population groups for covid-19 vaccination, based on in-hospital risk of death, by using Extreme Gradient Boosting Machine Learning (ML) algorithm. We performed a retrospective cohort study comprising 49,197 patients (18 years or older), with RT-PCR-confirmed for covid-19, who were hospitalized in any of the 336 …

  • Factors associated with the length of hospital stay of women undergoing cesarean section

    Open Access•Samire Lopes Pereira, Thales Philipe Rodrigues Da Silva et al.•ARTICLE•Revista de Saúde Pública•2019

    OBJECTIVE: To evaluate whether age group, complications or comorbidities are associated with the length of hospitalization of women undergoing cesarean section. METHODS: A cross-sectional study was carried out between June 2012 and July 2017, with 64,437 women undergoing cesarean section and who did not acquire conditions during their hospital stay. Hospital discharge data were collected from national health institutions, using the Diagnosis-Rela…

  • Rasteira do destino

    Open Access•Ronaldo Costa Couto•ARTICLE•Revista USP•2005

  • Plano verão

    Open Access•José Sarney, Mailson Ferreira da Nóbrega et al.•ARTICLE•Brazilian Journal of Political…•1989

    Statement by President José Sarney

No prominent works on this page.

  • Plano verão

    Open Access•José Sarney, Mailson Ferreira da Nóbrega et al.•ARTICLE•Brazilian Journal of Political…•1989

    Statement by President José Sarney

  • Rasteira do destino

    Open Access•Ronaldo Costa Couto•ARTICLE•Revista USP•2005

  • Factors associated with the length of hospital stay of women undergoing cesarean section

    Open Access•Samire Lopes Pereira, Thales Philipe Rodrigues Da Silva et al.•ARTICLE•Revista de Saúde Pública•2019

    OBJECTIVE: To evaluate whether age group, complications or comorbidities are associated with the length of hospitalization of women undergoing cesarean section. METHODS: A cross-sectional study was carried out between June 2012 and July 2017, with 64,437 women undergoing cesarean section and who did not acquire conditions during their hospital stay. Hospital discharge data were collected from national health institutions, using the Diagnosis-Rela…

  • Covid-19 vaccination priorities defined on machine learning

    Open Access•Ronaldo Costa Couto, Tânia Moreira Grillo Pedrosa et al.•ARTICLE•Revista de Saúde Pública•2022

    OBJECTIVE: Defining priority vaccination groups is a critical factor to reduce mortality rates. METHODS: We sought to identify priority population groups for covid-19 vaccination, based on in-hospital risk of death, by using Extreme Gradient Boosting Machine Learning (ML) algorithm. We performed a retrospective cohort study comprising 49,197 patients (18 years or older), with RT-PCR-confirmed for covid-19, who were hospitalized in any of the 336 …

  • Development of a machine learning modelto estimate length of stay in coronaryartery bypass grafting

    Open Access•Ronaldo Costa Couto, Tânia Moreira Grillo Pedrosa et al.•ARTICLE•Revista de Saúde Pública•2024

    OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.METHODS: Three machine learning models (random forest, extreme gradient boosting and neural networks) and three traditional regression models (Poisson regression, linear regression, negative binomial regression) were trained in a dataset of 9,584 patient…

Computer Science (4 works) · Medicine (3 works) · Internal Medicine (2 works) · Internal Medicine (2 works) · Sepsis Diagnosis and Treatment (2 works) · 2019-20 coronavirus outbreak (1 works) · Artery (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Betacoronavirus (1 works)

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