Title: An intelligent model for diagnosis of breast cancer

Authors: Raj Kamal Kaur Grewal; Babita Pandey

Addresses: Department of Computer Science, Lovely Professional University, Phagwara, Punjab 144402, India ' Department of Computer Application, Lovely Professional University, Phagwara, Punjab 144402, India

Abstract: Breast cancer, the most common disease in India in comparison to the USA and China, is not easily diagnosed in its initial stage. Early diagnosis can increase chances of survival; therefore it is important to diagnose it at the initial stage. This study accordingly employs J48 algorithm and case-based reasoning to construct an intelligent integrated diagnosis model aiming to provide a comprehensive analytic framework to raise the accuracy of breast cancer diagnosis at two levels. At first level, J48 is deployed for classifying the dataset into malignant and benign cancer. At the second level, malignant cases are classified as ductal carcinoma in situ, lobular carcinoma in situ, invasive ductal carcinoma, invasive lobular carcinoma, and mucinous carcinoma using case-based reasoning. The implemented result shows that the intelligent diagnosis model is able to examine the breast cancer with considerable accuracy (98.25%) and helpful for making the decision regarding breast cancer diagnosis.

Keywords: breast cancer; data mining; case-based reasoning; CBR; J48.

DOI: 10.1504/IJHTM.2022.123572

International Journal of Healthcare Technology and Management, 2022 Vol.19 No.1, pp.1 - 14

Received: 08 Feb 2017
Accepted: 27 Jan 2018
Published online: 28 Jun 2022 *

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