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BreastCancerAnalysisusingMachineLearning Algorithm – A Comprehensive Study
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| Author:
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VIBITH S, DR.JOBIN CHRIST M C
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| Abstract:
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Breast cancer has been encountered as the 2nd biggest reason for cancer fatalities with women aging between 40 to 55 succeeding lung cancer. According to data from the national cancer registry, young women are showing an increased incidence of breast cancer with 48% of patients below 50 years of age. Bearing the emergency of this issue in mind, this paperwork comprehends several research articles that took breast cancer as their problem for analysis. In breast cancer research, the ML techniques could be employed for distinguishing and forecast cancer. These ML techniques could forecast whether cancer is malignant or benign. Hence in this work, an elaborate literature review has been done on the role of a machine learning algorithm in breast cancer investigation. Different algorithms of Machine Learning techniques that are applied by the medical researchers for an effective and early prediction and detection of cancer cells have been studied and introduced. The disparate machine learning algorithm that is taken for the review work is SVM (Support Vector Machine), ANN (Artificial Neural Networks), Bayesian networks (BN), and DT (Decision Trees). Hope this research article presents a clear idea to the researchers working in this area.
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| Keyword:
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Breast cancer, ANN (Artificial Neural Networks), Support Vector Machine (SVM), Bayesian networks (BN), Decision Trees (DT)
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| EOI:
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.04.521
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| Download:
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Request For Article
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