LAUSR

Artificial Intelligence (AI) is a fascinating discipline that has captured our imagination since its birth in the 1950s [1]. Its function in society’s life has grown exponentially in the last decade, to a point where many of its manifestations such as face recognition or digital voice assistants are taken for granted and generate little or no astonishment in everyday users. Interest for AI application in health care began in the 1990s and soon turned to oncology. Given the large number of women diagnosed with breast cancer every year, this field is an optimal setting for the development of a technology largely based on processing significant amounts of data. Computer-aided detection (CAD) was the first software announced for clinical use in breast cancer diagnosis, and was burdened with significant expectations which were not entirely met since its introduction in the late 1990s [2]. This technology relied on algorithms programmed to analyze digital mammograms in search of the same features of malignancy that radiologists look for when reading an exam (i.e. shape, size, asymmetry etc): ‘old’ AI was therefore conceived as an enhancement of human intelligence that could be matched with the artificial benefit of processing large quantities of data. Despite encouraging initial results, years of CAD clinical application revealed no significant improvement in comprehensive screening performance, and general hype deflated until a new deep learning (DL) revolution generated a second wave of enthusiasm from the early 2010s [3].