Efficient Bioinspired Feature Selection and Machine Learning Based Framework Using Omics Data and Biological Knowledge Data Bases in Cancer Clinical Endpoint Prediction-Reference-Cited by-同舟云学术

Efficient Bioinspired Feature Selection and Machine Learning Based Framework Using Omics Data and Biological Knowledge Data Bases in Cancer Clinical Endpoint Prediction

Published:2023 Issue: Volume:11 Page:2674-2699
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zenbout Imene¹^ORCID,Bouramoul Abdelkrim¹,Meshoul Souham²,Amrane Mounira³

Affiliation:

1. Department of Fundamental Informatics and Its Application, MISC Laboratory, Constantine 2 University Abdelhamid Mehri, Constantine, Algeria

2. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

3. Biochemistry Department, Setif University Hospital, University Ferhat Abbas Setif 1, Setif, Algeria

Funder

Princess Nourah Bint Abdulrahman University Researchers Supporting Project through Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10006725.pdf?arnumber=10006725

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5. Feature selection and analysis on correlated gas sensor data with recursive feature elimination

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