ABSTRACT
In Asian women, breast cancer is the most common cause of cancer-related fatalities, and recently, it has overtaken cervical cancer in terms of prevalence among women. Using logistic regression, a statistical prediction machine learning method is used for diagnosing breast cancer. This chapter aims to analyze, evaluate, and compare the effectiveness of the existing breast cancer imaging schemes, including ultrasound, mammography, and magnetic resonance imaging techniques. Breast cancer feature values are gathered, tabulated, and evaluated using the logistic regression algorithm, an intrinsic tool of XAI to compare the proposed modalities. The tabulated data shows that MRI has significantly greater sensitivity values than other imaging modalities, including mammography and ultrasound imaging, which may be unsuccessful in individuals with a history of cancer and may not be able to detect some masses in the body.
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