Chronic diseases monitoring and diagnosis system based on features selection and machine learning predictive models-Reference-Cited by-同舟云学术

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Chronic diseases monitoring and diagnosis system based on features selection and machine learning predictive models

Published:2022-05-23 Issue:13 Volume:26 Page:6175-6199
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

EL-Rahman Sahar A.,Saleh Alluhaidan Ala,AlRashed Reem A.,AlZunaytan Duna N.

Funder

Princess Nourah Bint Abdulrahman University

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-022-07130-8.pdf

Reference72 articles.

1. Abbas S, Jalil Z, Javed AR, Batool I, Khan MZ, Noorwali A, Gadekallu TR, Akbar A (2021) BCD-WERT: a novel approach for breast cancer detection using whale optimization-based efficient features and an extremely randomized tree algorithm. PeerJ Computer Science 7:e390. https://doi.org/10.7717/peerj-cs.390

2. Abbasi R, Moradi M, Molaeezadeh S (2014) Long-term prediction of blood pressure time series using multiple fuzzy functions. In: 2014 21st iranian conference on biomedical engineering, ICBME 2014. https://doi.org/10.1109/ICBME.2014.7043906

3. Alassaf RA, Alsulaim KA, Alroomi NY, Alsharif NS, Aljubeir MF, Olatunji SO, …, Alturayeif NS (2018) “Preemptive diagnosis of chronic kidney disease using machine learning techniques.” 2018 International conference on innovations in information technology (IIT). DOI: https://doi.org/10.1109/innovations.2018.8606040

4. Alelyani S, Tang J, Liu H (2013) “Feature Selection for Clustering: A Review”

5. Alimran A, Amin M, Johora F (2018) “Classification of Chronic kidney disease using logistic regression, feedforward neural network and wide & deep learning”, International conference on innovation in engineering and technology (ICIET)

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