Earlier diagnosis of breast cancer using e- health file with hybrid machine learning algorithms
Department of Computer Science, Alagappa University, Tamil Nadu, India.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2022, 07(02), 212-219.
Article DOI: 10.30574/wjaets.2022.7.2.0163
Publication history:
Received on 08 November 2022; revised on 21 December 2022; accepted on 24 December 2022
Abstract:
Breast Cancer denotes the major disease which makes a high range of deaths worldwide. Earlier forecasting of breast cancer can help the breast cancer patients by improving their survival. Data mining methodologies and machine learning models are widely used in the health sector fields to offer effective diagnosis in various diseases. The main theme of this research work is to implement a hybrid approach of breast cancer predictions by using the SVM (Support vector Machine) and Naïve Bayes classifiers to predict the breast cancer using the E-Health file data of a patient. The proposed approach is aimed to offer the maximum accuracy than the existing approaches.
Keywords:
Diagnosis; Breast Cancer; E-Health; Machine Learning; SVM; Naïve Bayes; Hybrid
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