Artificial Intelligence for Early Breast Cancer Detection

Abstract

Breast cancer remains the most prevalent cancer among women globally, imposing significant economic and human burdens. Early detection is pivotal for improving patient outcomes and reducing treatment costs. This review explores the transformative role of artificial intelligence (AI) in the early detection of breast cancer, highlighting its integration into various aspects of health care. AI, particularly through ML and DL algorithms, enhances the accuracy and efficiency of imaging modalities such as mammography, ultrasound, and magnetic resonance imaging by identifying subtle abnormalities and personalizing risk assessments. Advanced AI models such as convolutional neural networks (CNNs) and vision transformers (ViTs) have demonstrated superior performance in analyzing complex medical images, leading to earlier diagnoses and reduced false positives and negatives. Additionally, AI-driven liquid biopsies offer minimally invasive alternatives for detecting circulating tumor DNA and other biomarkers, further advancing early detection capabilities. The review also addresses the diverse data types utilized in breast oncology, including electronic health records, digital pathology, radiomics, genomics, proteomics, and metabolomics, emphasizing the potential of multi-omic approaches for comprehensive cancer profiling. However, the clinical integration of AI faces challenges such as data quality, interoperability, workflow alignment, and ethical concerns including bias and data privacy. Future directions include the development of explainable AI models, digital twin technologies, implementation beyond detecting including clinical decision support, and the incorporation of multi-modal data to enhance diagnostic precision and personalized medicine. By addressing these challenges through multi-disciplinary collaboration, AI holds the promise of revolutionizing early breast cancer detection, ultimately improving patient outcomes and reducing the global burden of this pervasive disease.

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