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Analysis on Diagnosing Breast Cancer using Machine Learning Algorithms
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| Author:
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GOMATHI M, LOKESHWARI V, DR. KANDANALA MALLIKA, DR. BHARADWAJ VEDULA
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| Abstract:
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Breast cancer growth is a sort of disease found in the breast. Disease begins when cells start to develop wild. Breast cancer growth cells typically structure as a tumor felt as an irregularity. Breast malignancy happens in ladies. It is critical to locate that most breast protuberances are kind (acceptable cells) and not dangerous (cancer cells). Intermittent breast malignancy registration give the malady to be analyzed and treated before it causing observable side effects. AI computerizes the distinguishing proof of harmful cells and gives extensive advantages to the medical services frameworks. Computerized measure gives doctors to invest less energy in diagnosing and more opportunity for illnesses treatment, in this way it improves the proficiency of the recognition cycle. This examination work research the use of AI strategies for recognizing breast cancer growth by utilizing estimations of biopsied cells from ladies with irregular breast masses. It utilizes the Wisconsin Breast Cancer Diagnostic dataset from the UCI Machine Learning Repository. Various performance estimation methods are used to validate the methods used in the work.
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| Keyword:
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Breast cancer detection, Arrangement, Machine learning algorithm, WD, UCI Machine.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.SP1.463
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| Download:
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Request For Article
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