Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data
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 pred...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Proceedings |
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| Online Access: | https://www.mdpi.com/2504-3900/54/1/59 |
| _version_ | 1826994345714122752 |
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| author | Marta Moreno Abel Sousa Marta Melé Rui Oliveira Pedro G Ferreira |
| author_facet | Marta Moreno Abel Sousa Marta Melé Rui Oliveira Pedro G Ferreira |
| author_sort | Marta Moreno |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T16:32:08Z |
| format | Article |
| id | doaj.art-add057e662424394a755bacee31d9f43 |
| institution | Directory Open Access Journal |
| issn | 2504-3900 |
| language | English |
| last_indexed | 2025-02-18T09:17:19Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Proceedings |
| spelling | doaj.art-add057e662424394a755bacee31d9f432024-11-02T22:31:21ZengMDPI AGProceedings2504-39002020-09-015415910.3390/proceedings2020054059Predicting Gastric Cancer Molecular Subtypes from Gene Expression DataMarta Moreno0Abel Sousa1Marta Melé2Rui Oliveira3Pedro G Ferreira4Department of Computer Science, Faculty of Sciences, University of Porto, 4169-007 Porto, PortugalIpatimup—Institute of Molecular Pathology and Immunology of the University of Porto, 4200-465 Porto, PortugalLife Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034 Catalonia, SpainUniversity of Minho and INESC TEC, 4200-465 Porto, PortugalDepartment of Computer Science, Faculty of Sciences, University of Porto, 4169-007 Porto, PortugalStomach 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.https://www.mdpi.com/2504-3900/54/1/59gene expressiongastric cancerdisease classificationmachine learning |
| spellingShingle | Marta Moreno Abel Sousa Marta Melé Rui Oliveira Pedro G Ferreira Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data Proceedings gene expression gastric cancer disease classification machine learning |
| title | Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data |
| title_full | Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data |
| title_fullStr | Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data |
| title_full_unstemmed | Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data |
| title_short | Predicting Gastric Cancer Molecular Subtypes from Gene Expression Data |
| title_sort | predicting gastric cancer molecular subtypes from gene expression data |
| topic | gene expression gastric cancer disease classification machine learning |
| url | https://www.mdpi.com/2504-3900/54/1/59 |
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