Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data

• Tipo: Artigo em Revista Científica Internacional
• Data: 2020

Autores

Moreno, M (Autor) Outra; Sousa, A (Autor) Outra; Melé, M (Autor) Outra; Oliveira, R (Autor) Outra; G Ferreira, P (Autor) FCUP

Revista

Título: Proceedings

Vol. 54 Nº 1, Article 19

Página Final: 59

ISSN: 2504-3900

Editora: MDPI

Outras Informações

ID Authenticus: P-00V-9ZP

DOI: 10.3390/proceedings2020054059

Abstract (EN): <jats:p>Stomach cancer is a complex disease and one of the leading causes of cancer mortality in the world. With the view to improve patient diagnosis and prognosis, it has been stratified into four molecular subtypes. In this work, we compare the results of multiple machine learning algorithms for the prediction of stomach cancer molecular subtypes from gene expression data. Moreover, we show the importance of decorrelating clinical and technical covariates.</jats:p>

Idioma: Inglês

Tipo (Avaliação Docente): Científica