title: Multi-valued logic in breast cancer detection.
abstract: The aim of this paper is to determine the type of the breast cancer disease. The two classes of separation are malignant respectively benign. A multi-valued logic system (fuzzy system) was develop and applied in this classification. The system uses nine attributes as inputs that were scaled with an integer value in the range between 1 and 10. The attributes represent: 1. Clump Thickness, 2. Uniformity of Cell Size, 3. Uniformity of Cell Shape, 4. Marginal Adhesion, 5. Single Epithelial Cell Size, 6. Bare Nuclei, 7. Bland Chromatin, 8. Normal Nucleoli, 9. Mitoses. After training the system managed to get a good detection with an error less than 5%.
authors.affiliation: Department of Medical Informatics and Biostatistics, School of Medicine, Gr.T. Popa University of Medicine and Pharmacy, Iaşi.
authors.forename: L V
authors.initials: LV
authors.lastname: Boiculese
authors.forename: G
authors.initials: G
authors.lastname: Dimitriu
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D012680:Sensitivity and Specificity