• B Bennani-Baiti and P A T Baltzer.
• Universitätsklinik für Radiologie und Nuklearmedizin, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich. barbara.bennani-baiti@meduniwien.ac.at.
• Radiologe. 2020 Jan 1; 60 (1): 56-63.

BackgroundArtificial intelligence (AI) is increasingly applied in the field of breast imaging.ObjectivesWhat are the main areas where AI is applied in breast imaging and what AI and computer-aided diagnosis (CAD) systems are already available?Materials And MethodsBasic literature and vendor-supplied information are screened for relevant information, which is then pooled, structured and discussed from the perspective of breast imaging.ResultsOriginal CAD systems in mammography date almost 25 years back. They are much more widely applied in the United States than in Europe. The initial CAD systems exhibited limited diagnostic abilities and disproportionally high rates of false positive results. Since 2012, deep learning mechanisms have been applied and expand the application possibilities of AI.ConclusionTo date there is no algorithm that has beyond doubt been proven to outperform double reporting by two certified breast radiologists. AI could, however, in the foreseeable future, take over the following tasks: preselection of abnormal examinations to substantially reduce workload of the radiologists by either excluding normal findings from human review or by replacing the double reader in screening. Furthermore, the establishment of radio-patho-genomic correlations and their translation into clinical practice is hardly conceivable without AI.

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