Breast cancer is the most common life-threatening cancer in women and one of the leading causes of death. Early … diagnosis is one of the best defenses against the spread of breast cancer. Machine learning (ML) tools are now available for … cancer detection and prediction. This study presents a comparative assessment of machine learning models for diagnosing …

Breast cancer is a disease characterised by abnormal cell growth in the breast, with various types and unique … cancer. This study utilises the widely-used Wisconsin Breast Cancer Dataset (WBCD) from the University of California Irvine …, providing insights into different aspects of breast cancer. A stacked ensemble classifier is proposed to evaluate the …

analytics, assisting radiologists with a second opinion on cancer diagnosis. In this study, we explore two modalities of breast …

cancer detection. A knowledge base for training the DL models is constructed by combining different dermoscopic datasets … skin cancer. The performance of the trained models is investigated for multiclass and binary classification tasks. The …

Breast cancer is a major health issue for women all over the world. Effective care and better patient outcomes depend … emerged as potential ways to predict and classify breast cancer risk. This paper aims to investigate the feasibility of using … ensemble learning and big data fusion for risk prediction and categorization of breast cancer. The key focus is building a …