Abstract: Breast cancer is a profound global health challenge for women, where early detection is critical for saving lives, and while mammography is the standard screening tool, the manual interpretation of these images is a complex and often subjective task that can sometimes lead to errors. To address this, machine learning algorithms are now being developed as powerful aids, capable of analysing mammograms with advanced image processing to automatically identify subtle signs of malignancy, and by training these models on extensive datasets, we can create systems that achieve remarkable accuracy, offering a reliable, complementary tool that enhances traditional diagnostics and holds the transformative potential to improve early detection rates and patient outcomes worldwide.
Keywords: Machine Learning, Image Processing, Segmentation, Early Detection, Artificial Intelligence.
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DOI:
10.17148/IJARCCE.2025.14825
[1] Darshan R, Ananya, Darshan M, Inchara R, Latha S, "BREAST CANCER DETECTION FROM MAMMOGRAM USING MACHINE LEARNING ALGORITHMS," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14825
