{"id":1489,"date":"2025-02-05T20:11:11","date_gmt":"2025-02-05T20:11:11","guid":{"rendered":"https:\/\/www.lunit.io\/publication\/performance-of-two-deep-learning-based-ai-models-for-breast-cancer-detection-and-localization-on-screening-mammograms-from-breastscreen-norway\/"},"modified":"2025-11-02T12:54:58","modified_gmt":"2025-11-02T12:54:58","slug":"performance-of-two-deep-learning-based-ai-models-for-breast-cancer-detection-and-localization-on-screening-mammograms-from-breastscreen-norway","status":"publish","type":"publication","link":"https:\/\/www.lunit.io\/en\/publication\/performance-of-two-deep-learning-based-ai-models-for-breast-cancer-detection-and-localization-on-screening-mammograms-from-breastscreen-norway\/","title":{"rendered":"Performance of Two Deep Learning-based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway"},"content":{"rendered":"

Performance of Two Deep Learning\u2013based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway<\/h3>\n

Marit A. Martiniussen, Marthe Larsen, Tone Hovda, Merete U. Kristiansen, Fredrik A. Dahl, Line Eikvil, Olav Brautaset, Atle Bj\u00f8rnerud, Vessela Kristensen, Marie B. Bergan, Solveig Hofvind<\/p>\n

Radiology: Artificial Intelligence, 2025<\/strong><\/p>\n

Abstract<\/strong>
\nTwo deep learning\u2013based artificial intelligence (AI) models, one commercially available and one in-house, showed good performance for stand-alone cancer detection on retrospective mammography screening data. AI markings on the mammograms corresponded well to the true cancer location.<\/p>\n

Purpose<\/strong>
\nTo evaluate cancer detection and marker placement accuracy of two artificial intelligence (AI) models developed for interpretation of screening mammograms.<\/p>\n

Materials and Methods<\/strong>
\nThis retrospective study included data from 129\u2009434 screening examinations (all female patients; mean age, 59.2 years \u00b1 5.8 [SD]) performed between January 2008 and December 2018 in BreastScreen Norway. Model A was commercially available and model B was an in-house model. Area under the receiver operating characteristic curve (AUC) with 95% CIs were calculated. The study defined 3.2% and 11.1% of the examinations with the highest AI scores as positive, threshold 1 and 2, respectively. A radiologic review assessed location of AI markings and classified interval cancers as true or false negative.<\/p>\n

Results<\/strong>
\nThe AUC value was 0.93 (95% CI: 0.92, 0.94) for model A and B when including screen-detected and interval cancers. Model A identified 82.5% (611 of 741) of the screen-detected cancers at threshold 1 and 92.4% (685 of 741) at threshold 2. Model B identified 81.8% (606 of 741) at threshold 1 and 93.7% (694 of 741) at threshold 2. The AI markings were correctly localized for all screen-detected cancers identified by both models and 82% (56 of 68) of the interval cancers for model A and 79% (54 of 68) for model B. At the review, 21.6% (45 of 208) of the interval cancers were identified at the preceding screening by either or both models, correctly localized and classified as false negative (n = 17) or with minimal signs of malignancy (n = 28).<\/p>\n

Conclusion<\/strong>
\nBoth AI models showed promising performance for cancer detection on screening mammograms. The AI markings corresponded well to the true cancer locations.<\/p>\n

Read the full paper<\/strong><\/a><\/p>\n","protected":false},"featured_media":0,"template":"","publication-oncology":[],"publication-region":[89],"publication-type":[],"radiology":[97,99,96],"class_list":["post-1489","publication","type-publication","status-publish","hentry","publication-region-europe","radiology-breast","radiology-earlier-detection-including-interval-cancers","radiology-lunit-insight"],"acf":[],"yoast_head":"\nPerformance of Two Deep Learning-based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway - Lunit<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.lunit.io\/en\/publication\/performance-of-two-deep-learning-based-ai-models-for-breast-cancer-detection-and-localization-on-screening-mammograms-from-breastscreen-norway\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Performance of Two Deep Learning-based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway - Lunit\" \/>\n<meta property=\"og:description\" content=\"Performance of Two Deep Learning\u2013based AI Models for Breast Cancer Detection and Localization on Screening Mammograms from BreastScreen Norway Marit A. 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