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Artificial intelligence in breast imaging

Artificial intelligence (AI) is becoming integrated into many aspects of our day -to -day life, whether its suggestions on movies we should consider, books we may be interested in reading or apparel that may suit our personal taste. In preclinical research, AI provides tools for rapid and robust evaluation of cancer cell and organoid phenotypes or data from small animal imaging. AI is particularly well suited to radiology where it affords opportunities to enhance the speed, accuracy and quality of image interpretation. Rather than eliminating the need for radiologists anytime soon, AI can serve as a valuable adjunct to them allowing resulting in more dependable interpretations of ever more complex technology used in radiology. However, integration of AI to clinical imaging workflows requires careful evaluation of associated ethical, legal, and regulatory challenges.

In this cross-journal collection, we welcome a wide range of articles on AI in breast imaging, including primary research articles, method-based articles, reviews, and perspectives. 

To express your interest to contribute, please contact the Editor-in-Chief of the respective journal:

Breast Cancer Research: Lewis A. Chodosh (chodosh@pennmedicine.upenn.edu)
Journal of Mammary Gland Biology and Neoplasia: Zuzana Koledova (koledova@med.muni.cz)
Breast Cancer Research & Treatment: William J. Gradishar (w-gradishar@northwestern.edu)

Participating journals:
Breast Cancer Research: Submit here

Breast Cancer Research and Treatment: Submit here

Journal of Mammary Gland Biology and Neoplasia: Submit here

There are currently no articles in this collection.