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

Grupo de Investigación en Inteligencia Artificial y Reconocimiento Facial (GIIAR)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	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
Subtítulo de la publicación alojada	Future Systems IHIET-FS 2021
Editores	Tareq Ahram, Redha Taiar
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	1002-1010
Número de páginas	9
ISBN (versión impresa)	9783030855390
DOI	https://doi.org/10.1007/978-3-030-85540-6_128
Estado	Publicada - 2022
Evento	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 Duración: 27 ago. 2021 → 29 ago. 2021

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	319

Conferencia

Conferencia	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
Ciudad	Virtual, Online
Período	27/08/21 → 29/08/21

Nota bibliográfica

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

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

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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. En 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).

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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.",

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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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Landivar, GEV, Arambulo, JAE, Martinez, MAQ & Vazquez, MYL 2022, Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. En 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).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

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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.

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KW - Machine Learning

KW - Medical data

KW - Multicriteria method

KW - Support aystem

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SN - 9783030855390

T3 - Lecture Notes in Networks and Systems

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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

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Y2 - 27 August 2021 through 29 August 2021

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Landivar GEV, Arambulo JAE, Martinez MAQ, Vazquez MYL. Machine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method. En Ahram T, Taiar R, editores, 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