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Initiale CAD-Systeme (computergest\u00fctzte Diagnostik) zeichneten sich durch eine limitierte diagnostische Aussagekraft mit \u00fcberproportionalen Raten falsch-positiver Befunde aus. Seit 2012 kommen Deep\u2013Learning-Algorithmen zum Einsatz und erweitern die Einsatzm\u00f6glichkeiten der KI.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Schlussfolgerung<\/jats:title>\n<jats:p>Derzeit gibt es keinen Algorithmus, der \u2013 nachweislich validiert \u2013 die Doppelbefundung durch zertifizierte Mammaradiologen \u00fcbertrifft. In der mittelbaren Zukunft ist jedoch die \u00dcbernahme von Aufgaben durch KI absehbar: So kann die Vorselektion abnormer Studien die Arbeitslast gerade in der Fr\u00fcherkennung substanziell verringern. Auch die Erfassung von komplexen radiopathogenomischen Zusammenh\u00e4ngen und besonders ihre Translation in die klinische Praxis ist ohne KI kaum denkbar.<\/jats:p>\n<\/jats:sec>","DOI":"10.1007\/s00117-019-00615-y","type":"journal-article","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T12:08:57Z","timestamp":1575634137000},"page":"56-63","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["K\u00fcnstliche Intelligenz in der Mammadiagnostik","Artificial intelligence in the diagnosis of breast cancer"],"prefix":"10.1007","volume":"60","author":[{"given":"B.","family":"Bennani-Baiti","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P. A. 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