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Hamid Moghaddasi
Department of Health Information Management and Medical Informatics, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Research Article
Comparing the Efficiency of Diagnostic Models of Breast Cancer, Using Genetic Algorithm and Multi-Layer Perceptron Models
Author(s): Hamid Moghaddasi, Reza Rabie and Solmaz Sohrabie*
Background and objective: Breast cancer has become a common cancer in women. The early diagnosis of breast cancer has beneficial effects on the life patients. Due to difficulties in the disease, data mining techniques could help to facilitate the diagnosis, the current study amid to compare the efficiency of Genetic Algorithm (GA) and Multi- Layer Perceptron (MLP) in the diagnosis of the breast cancer. Methods: The database used in this paper is provided by Tehran university of Motamed Cancer Institute (MCI) breast cancer research center. This database included 7,625 records; there were 4,008 patients (52.4%) with breast cancers (malignant) and the remaining 3,617 patients (47.6%) without breast cancers (benign). GA and MLP models were developed using 14 fields (risk factor) of the database. The present study divided the data.. View more»