Artificial Intelligence and Advanced Imaging Techniques for Early and Precision Detection of Breast Cancer

Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide. Early and accurate detection is crucial for improving patient prognosis and enabling personalized treatment strategies. Recent advances in machine learning, deep learning, and image processing, combined with state-of-the-art imaging technologies such as digital mammography, MRI, ultrasound, and tomosynthesis, are opening up new possibilities for more sensitive, specific, and interpretable cancer diagnostics.

This Research Topic aims to highlight the latest developments in AI-driven algorithms, computer-aided diagnosis, and multimodal image analysis, as well as their integration into clinical workflows for early detection and precision medicine in breast cancer care. By gathering contributions from computational, biomedical, and clinical research communities, this Research Topic seeks to foster interdisciplinary collaboration and support the translation of innovative technologies into practice.

Submissions are welcomed on novel algorithmic advances, validation studies, translational research, and real-world clinical applications that address all stages of the imaging-based diagnostic pathway for breast cancer.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Artificial Intelligence, Breast Cancer Detection, Medical Imaging, Deep Learning, Early Diagnosis

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.