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. 2019 Apr 22;32(4):625–637. doi: 10.1007/s10278-019-00192-5

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© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Fig. 9 — Recent improvement in cmAssist stand-alone efficacy. cmAssist’s stand-alone combined efficacy (for both micro-calcifications and masses), based on two separate datasets are shown: a the CureMetrix quarantined test dataset consisting of 836 normal studies, 126 biopsy-proven micro-calcification cancer studies, and 323 biopsy-proven mass cancer studies, and b the 122 cases in the present study (90 biopsy-proven cancer studies and 32 normal studies). The green and blue curves represent the cmAssist efficacies at the time of the Readers study and at the time of current writing, respectively. AI-CAD, artificial intelligence-based computer-aided detection; CC (CC view only), ‘cranial-caudal’ view; CDR; cancer detection rate; cmAssist, prototype AI-CAD software from CureMetrix, Inc.; LCC, the left ‘cranial-caudal’; LMLO, the left ‘Mediolateral-Oblique’; neuScore, cmAssist quantitative score results (scale of 0–100); RCC, the right ‘cranial-caudal’; RMLO, the left ‘mediolateral-oblique’