A Framework for Modeling Critical Success Factors in the Selection of Machine Learning Algorithms for Breast Cancer Recognition

Miguel Angel Quiroz Martinez, Eddy Raul Montenegro Marin, Galo Enrique Valverde Landivar, Maikel Yelandi Leyva Vazquez

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Analysis of critical success factors allows software development organizations to focus on the factors to be successful. Selecting and implementing an algorithm for bosom cancer recognition could be hard. In this paper, a framework for modeling and analysis of success factors for the selection of Machine Learning methods used for the recognition of bosom cancer is presented. The objective is to analyze critical success factors in Machine Learning techniques selection for bosom cancer recognition built on Fuzzy Mental Maps. A group of common ML algorithms is presented in conjunction with the success factors. An analysis through measures calculation is presented in a case study. It was concluded that relevant factors for the selection of ML algorithms in the recognition of bosom cancer are: Selection of an ML algorithm according to the results, the study of ML algorithms tested in bosom cancer, obtaining and analyzing algorithm results.

Idioma originalInglés
Título de la publicación alojadaHuman 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 alojadaFuture Systems IHIET-FS 2021
EditoresTareq Ahram, Redha Taiar
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas874-881
Número de páginas8
ISBN (versión impresa)9783030855390
DOI
EstadoPublicada - 2022
Evento5th 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. 202129 ago. 2021

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen319
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389

Conferencia

Conferencia5th 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
CiudadVirtual, Online
Período27/08/2129/08/21

Nota bibliográfica

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

Huella

Profundice en los temas de investigación de 'A Framework for Modeling Critical Success Factors in the Selection of Machine Learning Algorithms for Breast Cancer Recognition'. En conjunto forman una huella única.

Citar esto