Optimizing Predictive Models and Streamlining Feature Selection Process In Oncology-Reference-Cited by-同舟云学术

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Optimizing Predictive Models and Streamlining Feature Selection Process In Oncology

Published:2024-05-24 Issue: Volume:11 Page:233-238
ISSN:
Container-title:2024 IEEE 14th Symposium on Computer Applications & Industrial Electronics (ISCAIE)
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Author:

Subrmanian Kavalvizhi¹,Faye Ibrahima²,Thangarasu Gunasekar³,Kannan K Nattar⁴

Affiliation:

1. Saveetha School of Engineering, MAHSA University, Universiti Teknologi PETRONAS, Saveetha Institute of Medical and Technical Sciences, Malaysia,Faculty of Engineering and IT,Deptartment of Applied Science,Chennai

2. Universiti Teknologi PETRONAS,Department of Fundamental & Applied Science,Perak,Malaysia

3. Saveetha School of Engineering Inernational Medical Univeristy, Saveetha Institute of Medical and Technical Sciences, Malaysia,Centre of Digital Health and Health Informatics,Chennai

4. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10576198/10576206/10576328.pdf?arnumber=10576328

Reference12 articles.

1. Complex predictive analysis for health care: a comprehensive review

2. D-PPSOK clustering algorithm with data sampling for clustering big data analysis

3. Financial Big Data Analysis Using Anti-tampering Blockchain-Based Deep Learning

4. Categorical Data Clustering Using Meta Heuristic Link-Based Ensemble Method

5. Classification of DNA microarray gene expression Leukaemia data through ABC and CNN method;Wahid;International Journal of Intelligent Systems and Applications in Engineering,2023

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