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 original | Inglés |
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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 | 874-881 |
Número de páginas | 8 |
ISBN (versión impresa) | 9783030855390 |
DOI | |
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 |
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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 |
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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.