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. 2021 Mar 4;19:55. doi: 10.1186/s12916-021-01928-3

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — Concordance statistics for AI determination of CACV. a Correlation of expert and AI-calculated CACV volumes by Spearman’s method. R² = 0.792. Two-tailed ICC = 0.904 (95% CI 0.857–0.936), p = < 0.0001. α = 0.05. The AI and expert CACV volumes have an excellent agreement that reliably follows a generalized linear trend with few outliers. b Bland-Altman plot of the quantitative differences between AI and expert measurements of CACV volume. AI and expert have a mean volume difference of 65.96 for the agreement of CACV volume. The CACV-AI software accurately predicts the CACV volume within acceptable limits compared to the expert. c Concordance of expert and AI reads of CACV binned into CACV > 0 and CACV = 0 groups, representing patients with and without CACV, respectively. Expert and AI excellently agree (Cohen’s kappa = 0.846, 95% CI 0.726–0.965) about CACV status with excellent screening parameters (sensitivity = 0.929, specificity = 0.960). CAC-AI volume, coronary artery calcium-artificial intelligence volume; CAC-Expert volume, coronary artery calcium-expert volume; SD, standard deviation; PPV, positive predictive value; NPV, negative predictive value; CI, confidence interval