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British Journal of Cancer
|
March 30, 2021
Meta-learning reduces the amount of data needed to build AI models in oncology
Olivier Gevaert
Bioinformatics (Oxford, England)
|
January 23, 2015
MethylMix: an R package for identifying DNA methylation-driven genes
Olivier Gevaert
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|
February 21, 2013
Identifying master regulators of cancer and their downstream targets by integrating genomic and epigenomic features
Olivier Gevaert, Sylvia Plevritis
Bioinformatics (Oxford, England)
|
September 13, 2019
Deep learning with multimodal representation for pancancer prognosis prediction
Anika Cheerla, Olivier Gevaert
BMC Bioinformatics
|
January 15, 2017
MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation
Nikhil Cheerla, Olivier Gevaert
Genome Medicine
|
March 11, 2016
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets
Catherine R Planey, Olivier Gevaert
Expert Opinion on Medical Diagnostics
|
March 15, 2013
Prediction of cancer outcome using DNA microarray technology: past, present and future
Olivier Gevaert, Bart De Moor
Bioinformatics (Oxford, England)
|
July 10, 2019
Comparison of single and module-based methods for modeling gene regulatory networks
Mikel Hernaez, Charles Blatti, Olivier Gevaert
IEEE Journal of Biomedical and Health Informatics
|
July 25, 2022
Reliably Filter Drug-Induced Liver Injury Literature With Natural Language Processing and Conformal Prediction
Xianghao Zhan, Fanjin Wang, Olivier Gevaert
Journal of Biomedical Informatics
|
June 20, 2017
Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)
Maryam Panahiazar, Michel Dumontier, Olivier Gevaert
Page
of 18
Search research articles
Search
Showing results (1-10 of 180) with videos related to
Sort By:
Page
of 18
British Journal of Cancer
|
March 30, 2021
Meta-learning reduces the amount of data needed to build AI models in oncology
Olivier Gevaert
Bioinformatics (Oxford, England)
|
January 23, 2015
MethylMix: an R package for identifying DNA methylation-driven genes
Olivier Gevaert
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|
February 21, 2013
Identifying master regulators of cancer and their downstream targets by integrating genomic and epigenomic features
Olivier Gevaert, Sylvia Plevritis
Bioinformatics (Oxford, England)
|
September 13, 2019
Deep learning with multimodal representation for pancancer prognosis prediction
Anika Cheerla, Olivier Gevaert
BMC Bioinformatics
|
January 15, 2017
MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation
Nikhil Cheerla, Olivier Gevaert
Genome Medicine
|
March 11, 2016
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets
Catherine R Planey, Olivier Gevaert
Expert Opinion on Medical Diagnostics
|
March 15, 2013
Prediction of cancer outcome using DNA microarray technology: past, present and future
Olivier Gevaert, Bart De Moor
Bioinformatics (Oxford, England)
|
July 10, 2019
Comparison of single and module-based methods for modeling gene regulatory networks
Mikel Hernaez, Charles Blatti, Olivier Gevaert
IEEE Journal of Biomedical and Health Informatics
|
July 25, 2022
Reliably Filter Drug-Induced Liver Injury Literature With Natural Language Processing and Conformal Prediction
Xianghao Zhan, Fanjin Wang, Olivier Gevaert
Journal of Biomedical Informatics
|
June 20, 2017
Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)
Maryam Panahiazar, Michel Dumontier, Olivier Gevaert
Page
of 18