Knowledge Discovery About Cancer Based on Fuzzy Predicates

Miguel Angel Quiroz Martinez; Christian Rene Vargas Alava; Monica Daniela Gomez Rios; Maikel Yelandi Leyva Vazquez

doi:10.1007/978-3-030-80624-8_31

Knowledge Discovery About Cancer Based on Fuzzy Predicates

Miguel Angel Quiroz Martinez, Christian Rene Vargas Alava, Monica Daniela Gomez Rios, Maikel Yelandi Leyva Vazquez

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

Resumen

Knowledge discovery information was analyzed in references regarding the health area. The problem is the lack of a generalized classification of cancer-based on fuzzy predicates, the challenge is the extraction of information from a data set. The objective is to perform a fuzzy predicate based on cancer knowledge discovery analysis to find time optimization of data and results. Empirical - analytical research with a quantitative approach was applied, its method is quasi-experimental and the technique of sampling a specific group of references was used. The application of materials resulted in an Analysis of the relationship between variables, a correlation between Monoplot, and Similarities between observations. It was concluded that the discovery of knowledge generates new quantitative information on the correlations between the attributes belonging to a data set; We use Principal Component Analysis which is a knowledge-based model to analyze positive or negative correlations between attributes or variables.

Idioma original	Inglés
Título de la publicación alojada	Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021
Editores	Tareq Z. Ahram, Waldemar Karwowski, Jay Kalra
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	242-250
Número de páginas	9
ISBN (versión impresa)	9783030806231
DOI	https://doi.org/10.1007/978-3-030-80624-8_31
Estado	Publicada - 2021
Evento	AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 - Virtual, Online Duración: 25 jul. 2021 → 29 jul. 2021

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	271

Conferencia

Conferencia	AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021
Ciudad	Virtual, Online
Período	25/07/21 → 29/07/21

Nota bibliográfica

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1007/978-3-030-80624-8_31

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Citar esto

Martinez, M. A. Q., Alava, C. R. V., Rios, M. D. G., & Vazquez, M. Y. L. (2021). Knowledge Discovery About Cancer Based on Fuzzy Predicates. En T. Z. Ahram, W. Karwowski, & J. Kalra (Eds.), Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 (pp. 242-250). (Lecture Notes in Networks and Systems; Vol. 271). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-80624-8_31

Martinez, Miguel Angel Quiroz ; Alava, Christian Rene Vargas ; Rios, Monica Daniela Gomez et al. / Knowledge Discovery About Cancer Based on Fuzzy Predicates. Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. editor / Tareq Z. Ahram ; Waldemar Karwowski ; Jay Kalra. Springer Science and Business Media Deutschland GmbH, 2021. pp. 242-250 (Lecture Notes in Networks and Systems).

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title = "Knowledge Discovery About Cancer Based on Fuzzy Predicates",

abstract = "Knowledge discovery information was analyzed in references regarding the health area. The problem is the lack of a generalized classification of cancer-based on fuzzy predicates, the challenge is the extraction of information from a data set. The objective is to perform a fuzzy predicate based on cancer knowledge discovery analysis to find time optimization of data and results. Empirical - analytical research with a quantitative approach was applied, its method is quasi-experimental and the technique of sampling a specific group of references was used. The application of materials resulted in an Analysis of the relationship between variables, a correlation between Monoplot, and Similarities between observations. It was concluded that the discovery of knowledge generates new quantitative information on the correlations between the attributes belonging to a data set; We use Principal Component Analysis which is a knowledge-based model to analyze positive or negative correlations between attributes or variables.",

keywords = "Cancer diagnosis, Correlation between variables, Fuzzy predicates, Knowledge discovery, Knowledge extraction",

author = "Martinez, {Miguel Angel Quiroz} and Alava, {Christian Rene Vargas} and Rios, {Monica Daniela Gomez} and Vazquez, {Maikel Yelandi Leyva}",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 ; Conference date: 25-07-2021 Through 29-07-2021",

year = "2021",

doi = "10.1007/978-3-030-80624-8_31",

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Martinez, MAQ, Alava, CRV, Rios, MDG & Vazquez, MYL 2021, Knowledge Discovery About Cancer Based on Fuzzy Predicates. En TZ Ahram, W Karwowski & J Kalra (eds.), Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. Lecture Notes in Networks and Systems, vol. 271, Springer Science and Business Media Deutschland GmbH, pp. 242-250, AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021, Virtual, Online, 25/07/21. https://doi.org/10.1007/978-3-030-80624-8_31

Knowledge Discovery About Cancer Based on Fuzzy Predicates. / Martinez, Miguel Angel Quiroz; Alava, Christian Rene Vargas; Rios, Monica Daniela Gomez et al.
Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. ed. / Tareq Z. Ahram; Waldemar Karwowski; Jay Kalra. Springer Science and Business Media Deutschland GmbH, 2021. p. 242-250 (Lecture Notes in Networks and Systems; Vol. 271).

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

TY - GEN

T1 - Knowledge Discovery About Cancer Based on Fuzzy Predicates

AU - Martinez, Miguel Angel Quiroz

AU - Alava, Christian Rene Vargas

AU - Rios, Monica Daniela Gomez

AU - Vazquez, Maikel Yelandi Leyva

PY - 2021

Y1 - 2021

N2 - Knowledge discovery information was analyzed in references regarding the health area. The problem is the lack of a generalized classification of cancer-based on fuzzy predicates, the challenge is the extraction of information from a data set. The objective is to perform a fuzzy predicate based on cancer knowledge discovery analysis to find time optimization of data and results. Empirical - analytical research with a quantitative approach was applied, its method is quasi-experimental and the technique of sampling a specific group of references was used. The application of materials resulted in an Analysis of the relationship between variables, a correlation between Monoplot, and Similarities between observations. It was concluded that the discovery of knowledge generates new quantitative information on the correlations between the attributes belonging to a data set; We use Principal Component Analysis which is a knowledge-based model to analyze positive or negative correlations between attributes or variables.

AB - Knowledge discovery information was analyzed in references regarding the health area. The problem is the lack of a generalized classification of cancer-based on fuzzy predicates, the challenge is the extraction of information from a data set. The objective is to perform a fuzzy predicate based on cancer knowledge discovery analysis to find time optimization of data and results. Empirical - analytical research with a quantitative approach was applied, its method is quasi-experimental and the technique of sampling a specific group of references was used. The application of materials resulted in an Analysis of the relationship between variables, a correlation between Monoplot, and Similarities between observations. It was concluded that the discovery of knowledge generates new quantitative information on the correlations between the attributes belonging to a data set; We use Principal Component Analysis which is a knowledge-based model to analyze positive or negative correlations between attributes or variables.

KW - Cancer diagnosis

KW - Correlation between variables

KW - Fuzzy predicates

KW - Knowledge discovery

KW - Knowledge extraction

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DO - 10.1007/978-3-030-80624-8_31

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SN - 9783030806231

T3 - Lecture Notes in Networks and Systems

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EP - 250

BT - Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021

A2 - Ahram, Tareq Z.

A2 - Karwowski, Waldemar

A2 - Kalra, Jay

PB - Springer Science and Business Media Deutschland GmbH

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Y2 - 25 July 2021 through 29 July 2021

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Martinez MAQ, Alava CRV, Rios MDG, Vazquez MYL. Knowledge Discovery About Cancer Based on Fuzzy Predicates. En Ahram TZ, Karwowski W, Kalra J, editores, Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. Springer Science and Business Media Deutschland GmbH. 2021. p. 242-250. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-80624-8_31