Prognosis of breast cancer based on a fuzzy classification method

L. Hedjazi; T. Kempowsky-Hamon; M. V. Le Lann; J. Aguilar-Martin

Prognosis of breast cancer based on a fuzzy classification method

L. Hedjazi
, T. Kempowsky-Hamon
, M. V. Le Lann
, J. Aguilar-Martin

LAAS CNRS
CNRS/Université Paul Sabatier
Polytechnic University of Catalonia

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

1 Citation (Scopus)

Abstract

Learning and classification techniques have shown their usefulness in the analysis of ana-cyto-pathological cancerous tissue data to develop a tool for the diagnosis or prognosis of cancer. The use of these methods to process datasets containing different types of data has become recently one of the challenges of many researchers. This paper presents the fuzzy classification method LAMDA with recent developments that allow handling this problem efficiently by processing simultaneously the quantitative, qualitative and interval data without any preamble change of the data nature as it must be generally done to use other classification methods. This method is applied to perform breast cancer prognosis on two real-world datasets and was compared with results previously published to prove the efficiency of the proposed method.

Original language	English
Title of host publication	BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics
Pages	123-130
Number of pages	8
Publication status	Published - 2010
Externally published	Yes
Event	1st International Conference on Bioinformatics, BIOINFORMATICS 2010 - Valencia, Spain Duration: 20 Jan 2010 → 23 Jan 2010

Publication series

Name	BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics

Conference

Conference	1st International Conference on Bioinformatics, BIOINFORMATICS 2010
Country/Territory	Spain
City	Valencia
Period	20/01/10 → 23/01/10

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Breast cancer prognosis
Classification
Fuzzy logic
Numerical and symbolic data

Cite this

@inproceedings{a0561fb01a9743469cf6bd9833453488,

title = "Prognosis of breast cancer based on a fuzzy classification method",

abstract = "Learning and classification techniques have shown their usefulness in the analysis of ana-cyto-pathological cancerous tissue data to develop a tool for the diagnosis or prognosis of cancer. The use of these methods to process datasets containing different types of data has become recently one of the challenges of many researchers. This paper presents the fuzzy classification method LAMDA with recent developments that allow handling this problem efficiently by processing simultaneously the quantitative, qualitative and interval data without any preamble change of the data nature as it must be generally done to use other classification methods. This method is applied to perform breast cancer prognosis on two real-world datasets and was compared with results previously published to prove the efficiency of the proposed method.",

keywords = "Breast cancer prognosis, Classification, Fuzzy logic, Numerical and symbolic data",

author = "L. Hedjazi and T. Kempowsky-Hamon and \{Le Lann\}, \{M. V.\} and J. Aguilar-Martin",

year = "2010",

language = "English",

isbn = "9789896740191",

series = "BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics",

pages = "123--130",

booktitle = "BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics",

note = "1st International Conference on Bioinformatics, BIOINFORMATICS 2010 ; Conference date: 20-01-2010 Through 23-01-2010",

}

Hedjazi, L, Kempowsky-Hamon, T, Le Lann, MV & Aguilar-Martin, J 2010, Prognosis of breast cancer based on a fuzzy classification method. in BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics. BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics, pp. 123-130, 1st International Conference on Bioinformatics, BIOINFORMATICS 2010, Valencia, Spain, 20/01/10.

Prognosis of breast cancer based on a fuzzy classification method. / Hedjazi, L.; Kempowsky-Hamon, T.; Le Lann, M. V. et al.
BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics. 2010. p. 123-130 (BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics).

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

TY - GEN

T1 - Prognosis of breast cancer based on a fuzzy classification method

AU - Hedjazi, L.

AU - Kempowsky-Hamon, T.

AU - Le Lann, M. V.

AU - Aguilar-Martin, J.

PY - 2010

Y1 - 2010

N2 - Learning and classification techniques have shown their usefulness in the analysis of ana-cyto-pathological cancerous tissue data to develop a tool for the diagnosis or prognosis of cancer. The use of these methods to process datasets containing different types of data has become recently one of the challenges of many researchers. This paper presents the fuzzy classification method LAMDA with recent developments that allow handling this problem efficiently by processing simultaneously the quantitative, qualitative and interval data without any preamble change of the data nature as it must be generally done to use other classification methods. This method is applied to perform breast cancer prognosis on two real-world datasets and was compared with results previously published to prove the efficiency of the proposed method.

AB - Learning and classification techniques have shown their usefulness in the analysis of ana-cyto-pathological cancerous tissue data to develop a tool for the diagnosis or prognosis of cancer. The use of these methods to process datasets containing different types of data has become recently one of the challenges of many researchers. This paper presents the fuzzy classification method LAMDA with recent developments that allow handling this problem efficiently by processing simultaneously the quantitative, qualitative and interval data without any preamble change of the data nature as it must be generally done to use other classification methods. This method is applied to perform breast cancer prognosis on two real-world datasets and was compared with results previously published to prove the efficiency of the proposed method.

KW - Breast cancer prognosis

KW - Classification

KW - Fuzzy logic

KW - Numerical and symbolic data

UR - https://www.scopus.com/pages/publications/77956375519

M3 - Conference proceeding

AN - SCOPUS:77956375519

SN - 9789896740191

T3 - BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics

SP - 123

EP - 130

BT - BIOINFORMATICS 2010 - Proceedings of the 1st International Conference on Bioinformatics

T2 - 1st International Conference on Bioinformatics, BIOINFORMATICS 2010

Y2 - 20 January 2010 through 23 January 2010

ER -

Prognosis of breast cancer based on a fuzzy classification method

Abstract

Publication series

Conference

UN SDGs

Keywords

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Cite this