Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method

Galo Enrique Valverde Landivar; Jonathan Andrés España Arambulo; Miguel Angel Quiroz Martinez; Maikel Yelandi Leyva Vazquez

doi:10.1007/978-3-030-85540-6_128

Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method

Galo Enrique Valverde Landivar
, Jonathan Andrés España Arambulo
, Miguel Angel Quiroz Martinez
, Maikel Yelandi Leyva Vazquez

Research Group in Artificial Intelligence and Facial Recognition (GIIAR)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

On the current information in the medical area related to cancer analysis, the selection of an optimal Machine Learning algorithm, based on a multicriteria method, for a system that supports clinical decisions is sought. As a methodology, exploratory research and the deductive method were applied to analyze the information from existing articles and ML algorithms' behavior applied in the area of medicine. This research and based on a use case of training and testing of the GLM, SVM, and ANN algorithms for selecting an algorithm. Addition-ally, for clinical decisions, and architecture prototype for medical data collection is presented resulted. Based on AHP and TOPSIS methods Support Vector Machine (SVM) is the best alternative.

Original language	English
Title of host publication	Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET
Subtitle of host publication	Future Systems IHIET-FS 2021
Editors	Tareq Ahram, Redha Taiar
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1002-1010
Number of pages	9
ISBN (Print)	9783030855390
DOIs	https://doi.org/10.1007/978-3-030-85540-6_128
State	Published - 2022
Event	5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and 6th International Conference on Human Interaction and Emerging Technologies: Future Systems, IHIET-FS 2021 - Virtual, Online Duration: 27 Aug 2021 → 29 Aug 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	319

Conference

Conference	5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and 6th International Conference on Human Interaction and Emerging Technologies: Future Systems, IHIET-FS 2021
City	Virtual, Online
Period	27/08/21 → 29/08/21

Bibliographical note

Funding Information:
This work has been supported by the GIIAR research group and the Universidad Polit?cnica Salesiana.

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Decision clinical
Machine Learning
Medical data
Multicriteria method
Support aystem

CACES Knowledge Areas

116A Computer Science

Access to Document

10.1007/978-3-030-85540-6_128

Cite this

Landivar, G. E. V., Arambulo, J. A. E., Martinez, M. A. Q., & Vazquez, M. Y. L. (2022). Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. In T. Ahram, & R. Taiar (Eds.), Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET: Future Systems IHIET-FS 2021 (pp. 1002-1010). (Lecture Notes in Networks and Systems; Vol. 319). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-85540-6_128

Landivar, Galo Enrique Valverde ; Arambulo, Jonathan Andrés España ; Martinez, Miguel Angel Quiroz et al. / Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET: Future Systems IHIET-FS 2021. editor / Tareq Ahram ; Redha Taiar. Springer Science and Business Media Deutschland GmbH, 2022. pp. 1002-1010 (Lecture Notes in Networks and Systems).

@inproceedings{eb197844f0bd40379341d3d8ab92580d,

title = "Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method",

abstract = "On the current information in the medical area related to cancer analysis, the selection of an optimal Machine Learning algorithm, based on a multicriteria method, for a system that supports clinical decisions is sought. As a methodology, exploratory research and the deductive method were applied to analyze the information from existing articles and ML algorithms' behavior applied in the area of medicine. This research and based on a use case of training and testing of the GLM, SVM, and ANN algorithms for selecting an algorithm. Addition-ally, for clinical decisions, and architecture prototype for medical data collection is presented resulted. Based on AHP and TOPSIS methods Support Vector Machine (SVM) is the best alternative.",

keywords = "Decision clinical, Machine Learning, Medical data, Multicriteria method, Support aystem",

author = "Landivar, \{Galo Enrique Valverde\} and Arambulo, \{Jonathan Andr{\'e}s Espa{\~n}a\} and Martinez, \{Miguel Angel Quiroz\} and Vazquez, \{Maikel Yelandi Leyva\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and 6th International Conference on Human Interaction and Emerging Technologies: Future Systems, IHIET-FS 2021 ; Conference date: 27-08-2021 Through 29-08-2021",

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doi = "10.1007/978-3-030-85540-6\_128",

language = "English",

isbn = "9783030855390",

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publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "1002--1010",

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Landivar, GEV, Arambulo, JAE, Martinez, MAQ & Vazquez, MYL 2022, Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. in T Ahram & R Taiar (eds), Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET: Future Systems IHIET-FS 2021. Lecture Notes in Networks and Systems, vol. 319, Springer Science and Business Media Deutschland GmbH, pp. 1002-1010, 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and 6th International Conference on Human Interaction and Emerging Technologies: Future Systems, IHIET-FS 2021, Virtual, Online, 27/08/21. https://doi.org/10.1007/978-3-030-85540-6_128

Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. / Landivar, Galo Enrique Valverde; Arambulo, Jonathan Andrés España; Martinez, Miguel Angel Quiroz et al.
Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET: Future Systems IHIET-FS 2021. ed. / Tareq Ahram; Redha Taiar. Springer Science and Business Media Deutschland GmbH, 2022. p. 1002-1010 (Lecture Notes in Networks and Systems; Vol. 319).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method

AU - Landivar, Galo Enrique Valverde

AU - Arambulo, Jonathan Andrés España

AU - Martinez, Miguel Angel Quiroz

AU - Vazquez, Maikel Yelandi Leyva

PY - 2022

Y1 - 2022

N2 - On the current information in the medical area related to cancer analysis, the selection of an optimal Machine Learning algorithm, based on a multicriteria method, for a system that supports clinical decisions is sought. As a methodology, exploratory research and the deductive method were applied to analyze the information from existing articles and ML algorithms' behavior applied in the area of medicine. This research and based on a use case of training and testing of the GLM, SVM, and ANN algorithms for selecting an algorithm. Addition-ally, for clinical decisions, and architecture prototype for medical data collection is presented resulted. Based on AHP and TOPSIS methods Support Vector Machine (SVM) is the best alternative.

AB - On the current information in the medical area related to cancer analysis, the selection of an optimal Machine Learning algorithm, based on a multicriteria method, for a system that supports clinical decisions is sought. As a methodology, exploratory research and the deductive method were applied to analyze the information from existing articles and ML algorithms' behavior applied in the area of medicine. This research and based on a use case of training and testing of the GLM, SVM, and ANN algorithms for selecting an algorithm. Addition-ally, for clinical decisions, and architecture prototype for medical data collection is presented resulted. Based on AHP and TOPSIS methods Support Vector Machine (SVM) is the best alternative.

KW - Decision clinical

KW - Machine Learning

KW - Medical data

KW - Multicriteria method

KW - Support aystem

UR - https://www.scopus.com/pages/publications/85115658965

U2 - 10.1007/978-3-030-85540-6_128

DO - 10.1007/978-3-030-85540-6_128

M3 - Conference contribution

AN - SCOPUS:85115658965

SN - 9783030855390

T3 - Lecture Notes in Networks and Systems

SP - 1002

EP - 1010

BT - Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET

A2 - Ahram, Tareq

A2 - Taiar, Redha

PB - Springer Science and Business Media Deutschland GmbH

T2 - 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and 6th International Conference on Human Interaction and Emerging Technologies: Future Systems, IHIET-FS 2021

Y2 - 27 August 2021 through 29 August 2021

ER -

Landivar GEV, Arambulo JAE, Martinez MAQ, Vazquez MYL. Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. In Ahram T, Taiar R, editors, Human Interaction, Emerging Technologies and Future Systems V - Proceedings of the 5th International Virtual Conference on Human Interaction and Emerging Technologies, IHIET 2021 and the 6th IHIET: Future Systems IHIET-FS 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 1002-1010. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-85540-6_128

Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Model for the early detection of breast cancer using medical images (MDTCM)

Cite this

Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Projects

Model for the early detection of breast cancer using medical images (MDTCM)

Cite this