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- W4313444799 abstract "In the Current era, due to explosion of population, early disease diagnosis has become a major concern medical research field. Due to breast cancer possibility of death is growing increasingly now days. From the previous analysis it has been disclosed that breast cancer has become second-most-severe disease as compare to other diseases. In early diagnosis and discovery of several diseases machine learning algorithm plays important role so that chance of patient’s survival will get increased. A reliable, effective, and quick reaction while also lowering the danger of death can be achieved using automated detection system which can be implemented using artificial intelligence or machine learning technique. In this research, we compare logistic regression, decision tree, random forest and K-nearest neighbor with the Neighbor Component Analysis (NCA) approach, which are all supervised machine learning techniques. In comparison with other algorithms, the automated system using KNN with NCA approach obtains high accuracy which is approximately 98.5%." @default.
- W4313444799 created "2023-01-06" @default.
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- W4313444799 date "2023-01-01" @default.
- W4313444799 modified "2023-10-16" @default.
- W4313444799 title "Breast Cancer Prediction Using Different Machine Learning Algorithm" @default.
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- W4313444799 doi "https://doi.org/10.1007/978-981-19-5443-6_37" @default.
- W4313444799 hasPublicationYear "2023" @default.
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