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SELF: a stacked-based ensemble learning framework for breast cancer classification by Amit Kumar Jakhar; Aman Gupta; Mrityunjay Singh is a Computer Science article available to read on EtoBox.
What is SELF: a stacked-based ensemble learning framework for breast cancer classification about?
Nowadays, breast cancer is the most prevalent and jeopardous disease in women after lung cancer. During the past few decades, a substantial amount of cancer cases have been reported throughout the world. Breast cancer has been a widely acknowledged category of cancer disease in women due to the lack of awareness. According to the world cancer survey report 2020, about 2.3 million cases and 685,000 deaths have been reported worldwide. As, the patient-doctor ratio (PDR) is very high; consequently, there is an utmost need for a machine-based intelligent breast cancer diagnosis system that can detect cancer at its early stage and cure it more efficiently. The plan is to assemble scientists in both the restorative and the machine learning fields to progress toward this clinical application. This paper presents SELF, a stacked-based ensemble learning framework, to classify breast cancer at an early stage from the histopathological images of tumor cells with computer-aided diagnosis tools. In this work, we use the BreakHis dataset with 7909 histopathological images and Wisconsin Breast Cancer Database (WBCD) with 569 instances for the performance evaluation of our proposed framework. We h
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It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Amit Kumar Jakhar; Aman Gupta; Mrityunjay Singh
- Publisher
- Springer Science and Business Media LLC
- Published
- 2023
- Language
- EN
- Field
- Computer Science (Physical Sciences)