Improving Breast Cancer Management with Artificial Intelligence: New Strategies and Perspective

Dear Colleagues,

Breast cancer is the most frequent cancer in women of all ages, accounting for over 2 million diagnoses annually. The need for personalized medicine has progressively changed management strategies for this disease, emphasizing the importance of a multi-disciplinary approach. Furthermore, the integration of artificial intelligence (AI) in conjunction with human expertise is emerging as fundamental to face all the challenges of this era.

While early diagnosis is widely recognized as the best way to improve survival rates, allowing for more effective and targeted treatments, a significant gap remains when it is not achieved, especially in women with dense breasts or at a high risk. AI has rapidly evolved over recent years and is now a powerful tool for physicians, making substantial contributions to breast cancer management across various aspects, including early detection, diagnosis, treatment planning and patient monitoring.

AI can be employed for image analysis, including mammography, ultrasound and MRI. It can also assist pathologists in analyzing biopsy slides and tissue samples more efficiently, improving the accuracy of cancer diagnosis. It can be useful for risk stratification in a screening setting by assessing a person’s risk of developing breast cancer based on their medical history, genetic factors and lifestyle choices. AI systems can help oncologists provide personalized treatment recommendations based on the specific characteristics of a patient’s tumor, such as size, stage and molecular markers. Additionally, AI models can predict a patient’s likelihood of survival and recurrence based on clinical and genomic data. With radiomics, which involves the extraction and analysis of a large number of quantitative features or data points from medical images, it is possible to identify patterns and correlation that may not be apparent to the human eye. Finally, AI can integrate data from electronic health records, medical imaging and genomic databases to provide a comprehensive patient profile, suggesting treatment options, potential drug adverse effects. It can also remotely monitor patients for signs of recurrence or treatment-related side effects, improving the quality of care and reducing hospital visits.

These applications wield the potential to elevate patient outcomes and alleviate the global burden of breast cancer, particularly among underserved populations beset by resource constraints and limited medical infrastructure.

This Special Issue aims to present and discuss these AI applications, highlighting the most recent strategies and providing new perspective for improving breast cancer diagnosis and survival, from diagnosis to therapy.

Original research articles and reviews are welcome. In particular, exploring the ethical issues and/or barriers related to the application of AI, the impact on clinical practice in terms of costs, confidentiality and disparities to access, as well as the relationship between its application and the human resources is of interest.

Papers investigating the research outcomes of AI are also welcome, as well as the impact of AI on public health.

Research areas may include (but not limited to) all the aforementioned topics.

I look forward to receiving your contributions.

Dr. Daniele Ugo Tari
Guest Editor

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• breast cancer
• breast cancer imaging
• breast cancer therapy
• care pathway
• medical treatment
• artificial intelligence
• public health
• radiomics
• predictive models
• risk assessment