Comparative Analysis to Predict Breast Cancer using Machine Learning Algorithms: A Survey

被引：17

作者：

Thomas, Tanishk ^{[1
]}

Pradhan, Nitesh ^{[1
]}

Dhaka, Vijaypal Singh ^{[2
]}

机构：

[1] Manipal Univ Jaipur, Dept Comp Sci & Engn, Jaipur, Rajasthan, India

[2] Manipal Univ Jaipur, Dept Comp & Commun Engn, Jaipur, Rajasthan, India

来源：

PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT-2020) | 2020年

关键词：

Artificial neural network; breast cancer; support vector machine; human disease;

D O I：

10.1109/icict48043.2020.9112464

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Breast Cancer is the second most dangerous cancer in the world. Most of the women die due to breast cancer not only in India but everywhere in the world. In 2011, USA stated that one in eight women suffered from cancer. Breast cancer develops due to the abnormal cell division in the breast itself which results in the formation of either benign or malignant cancer. So, it is very important to predict breast cancer at an early stage and by providing proper treatment, many lives can be saved. This paper aims to give a comparative study by applying different machine learning algorithms such as Support Vector Machine, K-Nearest Neighbour, Naive Bayes, Decision Tree, K-means and Artificial Neural Networks on Wisconsin Diagnostic dataset to predict breast cancer at an early stage.

引用

页码：192 / 196

页数：5

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