Machine learning integrated ensemble of feature selection methods followed by survival analysis for predicting breast cancer subtype specific miRNA biomarkers

Corrigendum: Identification of Breast Cancer Subtype Specific MicroRNAs Using Survival Analysis to Find Their Role in Transcriptomic Regulation

Frontiers in Genetics ◽

10.3389/fgene.2019.01382 ◽

2020 ◽

Vol 10 ◽

Author(s):

Michał Denkiewicz ◽

Indrajit Saha ◽

Somnath Rakshit ◽

Jnanendra Prasad Sarkar ◽

Dariusz Plewczynski

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Breast Cancer Subtype ◽

Identification of Breast Cancer Subtype Specific MicroRNAs Using Survival Analysis to Find Their Role in Transcriptomic Regulation

Frontiers in Genetics ◽

10.3389/fgene.2019.01047 ◽

2019 ◽

Vol 10 ◽

Cited By ~ 2

Author(s):

Michał Denkiewicz ◽

Indrajit Saha ◽

Somnath Rakshit ◽

Jnanendra Prasad Sarkar ◽

Dariusz Plewczynski

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Breast Cancer Subtype ◽

Advances in Intelligent Systems and Computing - Proceedings of International Conference on ICT for Sustainable Development ◽

A Comparative Analysis of Feature Selection Methods and Associated Machine Learning Algorithms on Wisconsin Breast Cancer Dataset (WBCD)

10.1007/978-981-10-0129-1_23 ◽

2016 ◽

pp. 215-224 ◽

Cited By ~ 3

Author(s):

Nileshkumar Modi ◽

Kaushar Ghanchi

Keyword(s):

Breast Cancer ◽

Machine Learning ◽

Feature Selection ◽

Comparative Analysis ◽

Learning Algorithms ◽

Breast Cancer Dataset ◽

Selection Methods ◽

Cancer Dataset

2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS) ◽

Breast cancer subtype identification using machine learning techniques

10.1109/iccabs.2014.6863912 ◽

2014 ◽

Cited By ~ 1

Author(s):

Forough Firoozbakht ◽

Iman Rezaeian ◽

Lisa Porter ◽

Luis Rueda

Keyword(s):

Breast Cancer ◽

Machine Learning ◽

Breast Cancer Subtype ◽

Machine Learning Techniques ◽

Learning Techniques ◽

Cancer Subtype ◽

Subtype Identification

Survival Analysis with the Integration of RNA-Seq and Clinical Data to Identify Breast Cancer Subtype Specific Genes

Lecture Notes in Computer Science - Pattern Recognition and Machine Intelligence ◽

10.1007/978-3-030-34872-4_16 ◽

2019 ◽

pp. 139-146

Author(s):

Indrajit Saha ◽

Somnath Rakshit ◽

Michal Denkiewicz ◽

Jnanendra Prasad Sarkar ◽

Debasree Maity ◽

...

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Clinical Data ◽

Breast Cancer Subtype ◽

Rna Seq ◽

A new feature selection approach for optimizing prediction models, applied to breast cancer subtype classification

2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) ◽

10.1109/bibm.2016.7822749 ◽

2016 ◽

Cited By ~ 1

Author(s):

Pham Quang Huy ◽

Alioune Ngom ◽

Luis Rueda

Keyword(s):

Breast Cancer ◽

Feature Selection ◽

Prediction Models ◽

Breast Cancer Subtype ◽

Subtype Classification ◽

Cancer Subtype ◽

Selection Approach ◽

New Feature ◽

Feature Selection Approach

Sentiment Analysis of Movie Reviews: A Study of Machine Learning Algorithms with Various Feature Selection Methods

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v5i9.113121 ◽

2017 ◽

Vol 5 (9) ◽

Cited By ~ 1

Author(s):

Rajwinder Kaur

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Sentiment Analysis ◽

Learning Algorithms ◽

Selection Methods

Are the estrogen receptor and SIRT3 axes of the mitochondrial UPR key regulators of breast cancer subtype determination according to age?

Aging and Cancer ◽

10.1002/aac2.12035 ◽

2021 ◽

Author(s):

Edmund Charles Jenkins ◽

Mrittika Chattopadhyay ◽

Doris Germain

Keyword(s):

Breast Cancer ◽

Estrogen Receptor ◽

Breast Cancer Subtype ◽

2018 International Symposium on Advanced Electrical and Communication Technologies (ISAECT) ◽

Feature Selection with Fast Correlation-Based Filter for Breast Cancer Prediction and Classification Using Machine Learning Algorithms

10.1109/isaect.2018.8618688 ◽

2018 ◽

Author(s):

Youness Khourdifi ◽

Mohamed Bahaj

Keyword(s):

Breast Cancer ◽

Machine Learning ◽

Feature Selection ◽

Learning Algorithms ◽

Cancer Prediction

Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance

Journal of Water Process Engineering ◽

10.1016/j.jwpe.2021.102033 ◽

2021 ◽

Vol 41 ◽

pp. 102033

Author(s):

Faramarz Bagherzadeh ◽

Mohamad-Javad Mehrani ◽

Milad Basirifard ◽

Javad Roostaei

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Wastewater Treatment ◽

Comparative Study ◽

Total Nitrogen ◽

Wastewater Treatment Plant ◽

Learning Algorithms ◽

Treatment Plant ◽

Selection Methods