A preliminary glossary of artificial intelligence in radiology

The use of artificial intelligence (AI) and deep learning is progressively gaining credibility in medicine, particularly within the radiological sciences (1). In particular, convolutional neural networks (CNN) can solve even complex cases and provide diagnoses within short time frames with a level of accuracy that occasionally surpasses the capabilities of radiologists. In this vein, data scientists and data engineers have appeared before radiology society conferences and delivered interesting talks regarding AI. As a result of the use of AI in radiology, previously unheard-of terminology has been introduced to the field that will become common language in the near future. Thus, this paper seeks to define many of these common terms for the benefit of radiology practitioners