Optimized Predictive Models in Health Care Using Machine Learning

6Feature Selection for Breast Cancer Detection

Kishan Sharda¹, Mandeep Singh Ramdev², Deepak Rawat³* and Pawan Bishnoi⁴

¹Associate Software Engineer, Neosoft Technologies, Rampur, India

²Department of CSE, Apex Institute of Technology, Rampur, India

³Department of Mathematics, Chandigarh University, Punjab, India

⁴Om Sterling Global University, Hisar, Haryana, India

Abstract

Breast cancer (BC) is the most prevalent disease affecting women worldwide. With an estimated 8.2 million fatalities, it is the leading cause of death worldwide. Several preprocessing and detection techniques are employed to enhance the effectiveness of breast cancer detection for early disease diagnosis. Currently, much effort is devoted to achieving effective optimization and detection strategies. It is challenging to identify breast cancer from the massive thermal dataset. Early identification of breast cancer is critical. Thermographic approaches are used in the treatment of breast cancer. Different areas of the affected area experience varying temperatures due to breast cancer. The performance of classification is enhanced by optimization. The photos were divided into healthy and malignant ones. The detection approach determines the most malignant area from the fewest picture preprocessing. The most crucial part of treatment is determining what kind of tumour it is. Tumors can be benign or malignant, with the latter being more harmful and potentially fatal. Therefore, a doctor’s ability to discern ...