Integration of aggressive bound tightening and Mixed Integer Programming for Cost-sensitive feature selection in medical diagnosis-Reference-Cited by-同舟云学术

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Integration of aggressive bound tightening and Mixed Integer Programming for Cost-sensitive feature selection in medical diagnosis

Published:2022-01 Issue: Volume:187 Page:115902
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Abdulla Mai^ORCID,Khasawneh Mohammad T.^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference52 articles.

1. Using Global Optimization to Improve Classification for Medical Diagnosis and Prognosis;Bagirov;Topics in Health Information Management,2001

2. Disjunctive programming;Balas,2010

3. On handling indicator constraints in mixed integer programming;Belotti;Computational Optimization and Applications,2016

4. Cost-sensitive feature selection for support vector machines;Benítez-Peña;Computers & Operations Research,2019

5. On support vector machines under a multiple-cost scenario;Benítez-Peña;Advances in Data Analysis and Classification,2019

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1. Medical diagnosis decision-making framework on the internet of medical things platform using hybrid learning;Wireless Networks;2023-11-04

2. Fuzzy rough feature selection using a robust non-linear vague quantifier for ordinal classification;Expert Systems with Applications;2023-11

3. Filter-based feature selection methods in the presence of missing data for medical prediction models;Multimedia Tools and Applications;2023-08-10

4. A decision-making system for medical diagnosis based on iterative nearest component analysis and optimized learning;2022 International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI);2022-11-06

5. EBBA: An Enhanced Binary Bat Algorithm Integrated with Chaos Theory and Lévy Flight for Feature Selection;Future Internet;2022-06-09

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