Generative AI in Breast Cancer Diagnosis and Treatment

This Collection aims to explore the burgeoning role of artificial intelligence (AI), specifically generative models, in revolutionizing the approach to diagnosing and treating breast cancer. This compilation seeks to present cutting-edge research and comprehensive reviews on the integration of generative AI technologies in the field of oncology, with a focus on breast cancer. It will cover a broad spectrum of topics ranging from the development of AI algorithms for the identification and classification of breast tumors in imaging studies, to the application of these technologies in predicting treatment responses and patient outcomes.

The Collection will delve into the use of AI for generating synthetic data - including medical images - for training purposes, enhancing the accuracy of diagnostic imaging, and personalizing treatment protocols. It will also explore the implications of AI in understanding the tumor microenvironment, potentially uncovering new therapeutic targets and improving the effectiveness of existing treatments.

Moreover, the Collection aims to address the ethical, regulatory, and technical challenges associated with implementing AI - especially generative AI - in clinical settings, ensuring patient safety, and maintaining data privacy. Contributions will include original research articles, reviews, case studies, and perspective pieces from leading experts in the fields of medical radiology and oncology.

Keywords: breast cancer, generative AI, artificial intelligence, diagnostic imaging, personalized medicine, synthetic data, oncology, machine learning