Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Moreno, M (Author) Other; Sousa, A (Author) Other; Melé, M (Author) Other; Oliveira, R (Author) Other; G Ferreira, P (Author) FCUP

Journal

Title: Proceedings

Vol. 54 No. 1, Article 19

Final page: 59

ISSN: 2504-3900

Publisher: MDPI

Other information

Authenticus ID: 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>

Language: English

Type (Professor's evaluation): Scientific