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Intelligent Fuzzy System to Predict the Wisconsin Breast Cancer Dataset.
Hernández-Julio, Yamid Fabián; Díaz-Pertuz, Leonardo Antonio; Prieto-Guevara, Martha Janeth; Barrios-Barrios, Mauricio Andrés; Nieto-Bernal, Wilson.
Afiliación
  • Hernández-Julio YF; Faculty of Economics, Administrative and Accounting Sciences, Universidad del Sinú Elías Bechara Zainúm, Montería 230002, Colombia.
  • Díaz-Pertuz LA; Faculty of Economics, Administrative and Accounting Sciences, Universidad del Sinú Elías Bechara Zainúm, Montería 230002, Colombia.
  • Prieto-Guevara MJ; Departamento de Ciencias Acuícolas-Medicina Veterinaria y Zootecnia (CINPIC), Universidad de Córdoba, Montería 230002, Colombia.
  • Barrios-Barrios MA; Systems Engineering Department, Universidad de la Costa, Barranquilla 080001, Colombia.
  • Nieto-Bernal W; Facultad de Ingeniería, Departamento de Ingeniería de Sistemas, Universidad del Norte, Barranquilla 80001, Colombia.
Int J Environ Res Public Health ; 20(6)2023 03 14.
Article en En | MEDLINE | ID: mdl-36982012
Decision Support Systems (DSSs) are solutions that serve decision-makers in their decision-making process. For the development of these intelligent systems, two primary components are needed: the knowledge database and the knowledge rule base. The objective of this research work was to implement and validate diverse clinical decision support systems supported by Mamdani-type fuzzy set theory using clustering and dynamic tables. The outcomes were evaluated with other works obtained from the literature to validate the suggested fuzzy systems for categorizing the Wisconsin breast cancer dataset. The fuzzy Inference Systems worked with different input features, according to the studies obtained from the literature. The outcomes confirm that most performance' metrics in several cases were greater than the achieved results from the literature for the output variable for the different Fuzzy Inference Systems-FIS, demonstrating superior precision.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Sistemas de Apoyo a Decisiones Clínicas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans País/Región como asunto: America do norte Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: Colombia Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Sistemas de Apoyo a Decisiones Clínicas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans País/Región como asunto: America do norte Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: Colombia Pais de publicación: Suiza