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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	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
Editors	Tareq Z. Ahram, Waldemar Karwowski, Jay Kalra
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	242-250
Number of pages	9
ISBN (Print)	9783030806231
DOIs	https://doi.org/10.1007/978-3-030-80624-8_31
State	Published - 2021
Event	AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 - Virtual, Online Duration: 25 Jul 2021 → 29 Jul 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	271

Conference

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

Bibliographical note

Funding Information:
This work has been supported by the GIIAR research group and the Universidad Polit?cnica Salesiana.

Funding Information:
Acknowledgments. This work has been supported by the GIIAR research group and the Universidad Politécnica Salesiana.

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Cancer diagnosis
Correlation between variables
Fuzzy predicates
Knowledge discovery
Knowledge extraction

CACES Knowledge Areas

8116A Information Systems

Access to Document

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

Cite this

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. In 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).

@inproceedings{49ebf9a6f7614807831640f53f8cb16e,

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",

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Martinez, MAQ, Alava, CRV, Rios, MDG & Vazquez, MYL 2021, Knowledge Discovery About Cancer Based on Fuzzy Predicates. in 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

UR - https://www.scopus.com/pages/publications/85112333620

U2 - 10.1007/978-3-030-80624-8_31

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

M3 - Conference contribution

AN - SCOPUS:85112333620

SN - 9783030806231

T3 - Lecture Notes in Networks and Systems

SP - 242

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

T2 - AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021

Y2 - 25 July 2021 through 29 July 2021

ER -

Martinez MAQ, Alava CRV, Rios MDG, Vazquez MYL. Knowledge Discovery About Cancer Based on Fuzzy Predicates. In Ahram TZ, Karwowski W, Kalra J, editors, 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

Knowledge Discovery About Cancer Based on Fuzzy Predicates

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Model for the early detection of breast cancer using medical images (MDTCM)

Cite this

Knowledge Discovery About Cancer Based on Fuzzy Predicates

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

CACES Knowledge Areas

Access to Document

Other files and links

Projects

Model for the early detection of breast cancer using medical images (MDTCM)

Cite this