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Role of artificial intelligence in cardiovascular risk prediction and outcomes: comparison of machine-learning and conventional statistical approaches for the analysis of carotid ultrasound features and intra-plaque neovascularization.
Johri AM, Mantella LE, Jamthikar AD, Saba L, Laird JR, Suri JS. Johri AM, et al. Among authors: jamthikar ad. Int J Cardiovasc Imaging. 2021 Nov;37(11):3145-3156. doi: 10.1007/s10554-021-02294-0. Epub 2021 May 29. Int J Cardiovasc Imaging. 2021. PMID: 34050838
A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography.
Jamthikar A, Gupta D, Khanna NN, Araki T, Saba L, Nicolaides A, Sharma A, Omerzu T, Suri HS, Gupta A, Mavrogeni S, Turk M, Laird JR, Protogerou A, Sfikakis PP, Kitas GD, Viswanathan V, Pareek G, Miner M, Suri JS. Jamthikar A, et al. Curr Atheroscler Rep. 2019 May 1;21(7):25. doi: 10.1007/s11883-019-0788-4. Curr Atheroscler Rep. 2019. PMID: 31041615 Review.
A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes.
Jamthikar A, Gupta D, Khanna NN, Saba L, Araki T, Viskovic K, Suri HS, Gupta A, Mavrogeni S, Turk M, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Kitas GD, Viswanathan V, Nicolaides A, Bhatt DL, Suri JS. Jamthikar A, et al. Cardiovasc Diagn Ther. 2019 Oct;9(5):420-430. doi: 10.21037/cdt.2019.09.03. Cardiovasc Diagn Ther. 2019. PMID: 31737514 Free PMC article.
Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited?
Saba L, Jamthikar A, Gupta D, Khanna NN, Viskovic K, Suri HS, Gupta A, Mavrogeni S, Turk M, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Kitas GD, Viswanathan V, Nicolaides A, Bhatt DL, Suri JS. Saba L, et al. Int Angiol. 2019 Dec;38(6):451-465. doi: 10.23736/S0392-9590.19.04267-6. Epub 2019 Nov 25. Int Angiol. 2019. PMID: 31782286 Free article. Review.
Nonlinear model for the carotid artery disease 10-year risk prediction by fusing conventional cardiovascular factors to carotid ultrasound image phenotypes: A Japanese diabetes cohort study.
Khanna NN, Jamthikar AD, Araki T, Gupta D, Piga M, Saba L, Carcassi C, Nicolaides A, Laird JR, Suri HS, Gupta A, Mavrogeni S, Kitas GD, Suri JS. Khanna NN, et al. Among authors: jamthikar ad. Echocardiography. 2019 Feb;36(2):345-361. doi: 10.1111/echo.14242. Epub 2019 Jan 9. Echocardiography. 2019. PMID: 30623485
35 results