A detailed review and critical analysis of various ML and DL algorithms utilized in early-stage BC assessment and detection demonstrates that XGBoost and ensemble/hybrid models currently yield the highest predictive precision.
The most important contributions from this review are a quantitative comparison of efficiency for edge versus cloud deployment, detection of dataset bias, and practical recommendations regarding infrastructure, regulatory pathways, and privacy-preserving federated learning.
Kennedy T. Chitiza, Abid Yahya, Nechibvute Action et al.· Discover Data· 0 citations
Breast cancer is one of the leading causes of cancer-related mortality worldwide, and despite advances in clinical diagnosis, challenges such as inconclusive imaging results and inter-observer variability highlight the need for complementary computational approaches to support early and accurate detection. In this stud...
Background: Breast cancer is the leading cause of cancer-related mortality in females, with 2.3 million new cases diagnosed annually. Machine learning (ML) algorithms have the potential to improve diagnostic accuracy through the analysis of high-dimensional data. However, the lack of standardized benchmarks across diff...
Ali A. Hamad, Naaman Omar· Charmo Journal of Natural Sc...· 0 citations
Cancer continues to be one of the leading causes of death worldwide, and the challenges of late detection and misdiagnosis are major factors that hinder survival rates. This paper addresses the critical issue of diagnosing cancer at advanced stages and misclassifies it by introducing an AI-driven framework aimed at ear...
Ibikunle Frank Ayoleke· Hensard Journal of Health Go...· 0 citations
A comprehensive Machine Learning framework that employs k-Nearest Neighbors, Random Forest, Logistic Regression, and Extreme Gradient Boosting algorithms to analyze a breast cancer dataset obtained from the UCI repository underscores the potential of ML-driven approaches in enhancing breast cancer diagnostics and contr...
Hani Attar, Jafar Ababneh, Waleed Alomoush et al.· International Journal of Com...· 0 citations
Breast cancer remains the most frequently diagnosed cancer and a leading cause of cancer death among women worldwide, so tools that support early and accurate detection are urgently needed. This review synthesizes a pool of one hundred studies, largely published between 2023 and 2026, on deep learning, ensemble learnin...
Abraham Temilade Olumide, Obe Olumide Olayinka, Akinwonmi Akintoba Emmanuel et al.· INTERNATIONAL JOURNAL OF MAT...· 0 citations
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