A new two-feature FAM-matrix classifier for breast cancer diagnosis

Tijana Ivancevic; Lakhmi Jain; Murk Bottema

doi:10.1109/KES.1999.820184

A new two-feature FAM-matrix classifier for breast cancer diagnosis

Tijana Ivancevic, Lakhmi Jain, Murk Bottema

College of Science and Engineering

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

7 Citations (Scopus)

Abstract

In this paper a fuzzy-logic FAM-matrix classifier is used for the classification (diagnosis) of breast cancer. It is implemented in `Mathematica 3.0' and tested on two features, radius and perimeter, from the Wisconsin breast cancer database. Sensitivity of FAM-matrix classifier is 94.29%, and specificity is 73.33%.

Original language	English
Title of host publication	1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems
Editors	L. C. Jain
Place of Publication	Piscataway, NJ, USA
Pages	305-308
Number of pages	4
DOIs	https://doi.org/10.1109/KES.1999.820184
Publication status	Published - 1999
Event	Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99) - Adelaide, Aust Duration: 31 Aug 1999 → 1 Sep 1999

Conference

Conference	Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99)
City	Adelaide, Aust
Period	31/08/99 → 1/09/99

Keywords

FAM
fuzzy associative memory
matrix
breast cancer

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10.1109/KES.1999.820184Licence: In Copyright

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Ivancevic, T, Jain, L & Bottema, M 1999, A new two-feature FAM-matrix classifier for breast cancer diagnosis. in LC Jain (ed.), 1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Piscataway, NJ, USA, pp. 305-308, Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99), Adelaide, Aust, 31/08/99. https://doi.org/10.1109/KES.1999.820184

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AU - Bottema, Murk

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AB - In this paper a fuzzy-logic FAM-matrix classifier is used for the classification (diagnosis) of breast cancer. It is implemented in `Mathematica 3.0' and tested on two features, radius and perimeter, from the Wisconsin breast cancer database. Sensitivity of FAM-matrix classifier is 94.29%, and specificity is 73.33%.

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KW - matrix

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A new two-feature FAM-matrix classifier for breast cancer diagnosis

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Keywords

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