WELLINGSON SILVA PAIVA
Projetos de Pesquisa
Unidades Organizacionais
Instituto Central, Hospital das Clínicas, Faculdade de Medicina
LIM/62 - Laboratório de Fisiopatologia Cirúrgica, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/45 - Laboratório de Fisiopatologia Neurocirúrgica, Hospital das Clínicas, Faculdade de Medicina
LIM/62 - Laboratório de Fisiopatologia Cirúrgica, Hospital das Clínicas, Faculdade de Medicina - Líder
LIM/45 - Laboratório de Fisiopatologia Neurocirúrgica, Hospital das Clínicas, Faculdade de Medicina
31 resultados
Resultados de Busca
Agora exibindo 1 - 10 de 31
bookPart Diagnóstico e Tratamento de Ferimentos Penetrantes Cranianos de Baixa Energia(2015) SANTO, Marcelo Prudente do Espírito; AMORIM, Robson Luis Oliveira de; PAIVA, Wellingson SilvabookPart Neuropatia Óptica Traumática(2015) AMORIM, Robson Luis Oliveira de; ANDRADE, Almir Ferreira de; BORGES, Rodrigo Almeida; PAIVA, Wellingson Silva- Machine learning and prediction of traumatic brain injury mortality(2022) SANTOS, J. G. R. P. dos; PAIVA, W. S.Traumatic brain injury is a “pandemic” disease, with alarming numbers each year around the world that accounts for significant healthcare, socioeconomic, and psychological issues in developing countries. The main issue is associated with the disability of affected subjects and reduction of the quality of life, work capacity, and life expectancy. Ability to estimate prognosis at admission is an important decision-making factor. Creating a model for traumatic brain injury evaluation is desired by many researchers. Classical models are based on two important trials: International Mission for Prognosis and Analysis of Clinical Trials and Corticosteroid randomization after significant head injury trial. Each one investigated more than 10,000 patients and this database helped build these two important models. Both are based on admission characteristics, while some other models were created based on clinical courses. Construction of a model involves a rigid protocol: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis statement recommendations for the reporting of prognostic models. The correct statistical tests must be correctly chosen to select appropriate variables. Machine learning for traumatic brain injury is an elaborate, methodological process that can be used as an example to build similar models for other neurological diseases. © 2022 Elsevier Inc. All rights reserved.
bookPart Neurocirurgia Minimamente Invasiva para Tumores Cerebrais(2015) MANDEL, Mauricio; PAIVA, Wellingson Silva; SILVA, Clemar Côrrea dabookPart Tumores do Tronco Cerebral no Adulto(2015) PAIVA, Wellingson SilvabookPart Hematomas Epidurais: Diagnóstico e Conduta(2015) NEVILLE, Iuri Santana; SOUSA JUNIOR, Leonardo de Moura; PAIVA, Wellingson Silva; FIGUEIREDO, Eberval Gadelha; ANDRADE, Almir Ferreira debookPart Hemorragia Subaracnóidea Traumática(2015) PAIVA, Wellingson Silva; AMORIM, Robson Luis Oliveira de; ANDRADE, Almir Ferreira debookPart Avaliação do Paciente em Coma na Sala de Emergência(2015) AMORIM, Robson Luis Oliveira de; PAIVA, Wellingson Silva; ANDRADE, Almir Ferreira debookPart CARACETRIZAÇÃO E CONDUTA NO TRAUMATISMO CRANIOENCEFÁLICO LEVE(2016) ANDRADE, Almir Ferreira de; PAIVA, Wellingson Silva; FIGUEIREDO, Eberval Gadelha; SANTOS, João Gustavo Rocha Peixoto dos; TEIXEIRA, Manoel JacobsenbookPart Hematoma Subdural Agudo(2015) AMORIM, Robson Luis Oliveira de; ANDRADE, Almir Ferreira de; BORGES, Rodrigo Almeida; PAIVA, Wellingson Silva; MANGINI, Nadia Nader