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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. 5 — Multivariate cardiovascular outcome modeling using clinical risk factors and CACV-AI volume as predictors in partial least squares regression (PLS). CACV-AI volume was the largest predictor of acute coronary syndrome/myocardial infarction, major adverse cardiac events (MACE), and percutaneous coronary intervention/coronary artery bypass grafting in 1 year of follow-up (AUC = 0.900, 0.911, 0.811, respectively). a Receiver-operator curves describing predictive power of individual cardiovascular outcomes. b Correlation biplots describing the magnitude and direction of associations of predictors with individual cardiovascular outcomes. c Model parameters. Variables with VIP > 1 and 95% CI significant from zero were considered important in the model. The models have a moderate fit and excellently predict cardiovascular events in 1 year of follow-up. ACS/MI, acute coronary syndrome/myocardial infarction; MACE, major adverse cardiac event; PCI, percutaneous coronary intervention; AUC, area under the curve; BMI, body mass index; HTN, hypertension; HLD, hyperlipidemia; VIP, variable importance projection; RMSE, root mean squared error; CI, confidence interval; CAC-AI Volume, coronary artery calcium-artificial intelligence volume; CAC-Expert volume, coronary artery calcium-expert volume