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- W4375947579 abstract "Image processing is a very vital part of many medical diagnosis. With the advent of more technologically advanced devices, machine learning implementation has also proven to be boon in the medical world for imaging related diagnosis. This paper aims to utilize different machine learning models to highlight its efficacy in the field of medical image analysis. The paper uses machine learning classifiers to classify breast cancer into malignant and benign using 31 attributes of the Wisconsin Breast Cancer Diagnostic dataset. Five different classifier models – Decision Trees, SVM, Naive Bayes, KNN and ANN were used to classify the tumors and it was observed and concluded that SVM model performed better with an accuracy of approximately 97.4% followed by ANN model with an accuracy of approximately 96.5%." @default.
- W4375947579 created "2023-05-10" @default.
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- W4375947579 date "2023-03-23" @default.
- W4375947579 modified "2023-09-29" @default.
- W4375947579 title "Application of Machine Learning Algorithms in Medical Image Analysis: A case study for Breast Cancer detection" @default.
- W4375947579 doi "https://doi.org/10.1109/spin57001.2023.10117210" @default.
- W4375947579 hasPublicationYear "2023" @default.
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