Cargando…

Potential and limitations of machine meta-learning (ensemble) methods for predicting COVID-19 mortality in a large inhospital Brazilian dataset

The majority of early prediction scores and methods to predict COVID-19 mortality are bound by methodological flaws and technological limitations (e.g., the use of a single prediction model). Our aim is to provide a thorough comparative study that tackles those methodological issues, considering mul...

Descripción completa

Detalles Bibliográficos
Autores principales: de Paiva, Bruno Barbosa Miranda, Pereira, Polianna Delfino, de Andrade, Claudio Moisés Valiense, Gomes, Virginia Mara Reis, Souza-Silva, Maira Viana Rego, Martins, Karina Paula Medeiros Prado, Sales, Thaís Lorenna Souza, de Carvalho, Rafael Lima Rodrigues, Pires, Magda Carvalho, Ramos, Lucas Emanuel Ferreira, Silva, Rafael Tavares, de Freitas Martins Vieira, Alessandra, Nunes, Aline Gabrielle Sousa, de Oliveira Jorge, Alzira, de Oliveira Maurílio, Amanda, Scotton, Ana Luiza Bahia Alves, da Silva, Carla Thais Candida Alves, Cimini, Christiane Corrêa Rodrigues, Ponce, Daniela, Pereira, Elayne Crestani, Manenti, Euler Roberto Fernandes, Rodrigues, Fernanda d’Athayde, Anschau, Fernando, Botoni, Fernando Antônio, Bartolazzi, Frederico, Grizende, Genna Maira Santos, Noal, Helena Carolina, Duani, Helena, Gomes, Isabela Moraes, Costa, Jamille Hemétrio Salles Martins, di Sabatino Santos Guimarães, Júlia, Tupinambás, Julia Teixeira, Rugolo, Juliana Machado, Batista, Joanna d’Arc Lyra, de Alvarenga, Joice Coutinho, Chatkin, José Miguel, Ruschel, Karen Brasil, Zandoná, Liege Barella, Pinheiro, Lílian Santos, Menezes, Luanna Silva Monteiro, de Oliveira, Lucas Moyses Carvalho, Kopittke, Luciane, Assis, Luisa Argolo, Marques, Luiza Margoto, Raposo, Magda Cesar, Floriani, Maiara Anschau, Bicalho, Maria Aparecida Camargos, Nogueira, Matheus Carvalho Alves, de Oliveira, Neimy Ramos, Ziegelmann, Patricia Klarmann, Paraiso, Pedro Gibson, de Lima Martelli, Petrônio José, Senger, Roberta, Menezes, Rochele Mosmann, Francisco, Saionara Cristina, Araújo, Silvia Ferreira, Kurtz, Tatiana, Fereguetti, Tatiani Oliveira, de Oliveira, Thainara Conceição, Ribeiro, Yara Cristina Neves Marques Barbosa, Ramires, Yuri Carlotto, Lima, Maria Clara Pontello Barbosa, Carneiro, Marcelo, Bezerra, Adriana Falangola Benjamin, Schwarzbold, Alexandre Vargas, de Moura Costa, André Soares, Farace, Barbara Lopes, Silveira, Daniel Vitorio, de Almeida Cenci, Evelin Paola, Lucas, Fernanda Barbosa, Aranha, Fernando Graça, Bastos, Gisele Alsina Nader, Vietta, Giovanna Grunewald, Nascimento, Guilherme Fagundes, Vianna, Heloisa Reniers, Guimarães, Henrique Cerqueira, de Morais, Julia Drumond Parreiras, Moreira, Leila Beltrami, de Oliveira, Leonardo Seixas, de Deus Sousa, Lucas, de Souza Viana, Luciano, de Souza Cabral, Máderson Alvares, Ferreira, Maria Angélica Pires, de Godoy, Mariana Frizzo, de Figueiredo, Meire Pereira, Guimarães-Junior, Milton Henriques, de Paula de Sordi, Mônica Aparecida, da Cunha Severino Sampaio, Natália, Assaf, Pedro Ledic, Lutkmeier, Raquel, Valacio, Reginaldo Aparecido, Finger, Renan Goulart, de Freitas, Rufino, Guimarães, Silvana Mangeon Meirelles, Oliveira, Talita Fischer, Diniz, Thulio Henrique Oliveira, Gonçalves, Marcos André, Marcolino, Milena Soriano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975879/
https://www.ncbi.nlm.nih.gov/pubmed/36859446
http://dx.doi.org/10.1038/s41598-023-28579-z