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For: Xu B, Kocyigit D, Grimm R, Griffin BP, Cheng F. Applications of artificial intelligence in multimodality cardiovascular imaging: A state-of-the-art review. Progress in Cardiovascular Diseases 2020;63:367-76. [DOI: 10.1016/j.pcad.2020.03.003] [Cited by in Crossref: 14] [Cited by in F6Publishing: 16] [Article Influence: 7.0] [Reference Citation Analysis]
Number Citing Articles
1 Haq IU, Chhatwal K, Sanaka K, Xu B. Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects. Vasc Health Risk Manag 2022;18:517-28. [PMID: 35855754 DOI: 10.2147/VHRM.S279337] [Reference Citation Analysis]
2 Krajcer Z. Artificial Intelligence in Cardiovascular Medicine: Historical Overview, Current Status, and Future Directions. Tex Heart Inst J 2022;49:e207527. [PMID: 35481866 DOI: 10.14503/THIJ-20-7527] [Reference Citation Analysis]
3 Thomas LB, Mastorides SM, Viswanadhan NA, Jakey CE, Borkowski AA. Artificial Intelligence: Review of Current and Future Applications in Medicine. Fed Pract 2021;38:527-38. [PMID: 35136337 DOI: 10.12788/fp.0174] [Reference Citation Analysis]
4 Lee S, Lam SH, Hernandes Rocha TA, Fleischman RJ, Staton CA, Taylor R, Limkakeng AT. Machine Learning and Precision Medicine in Emergency Medicine: The Basics. Cureus 2021;13:e17636. [PMID: 34646684 DOI: 10.7759/cureus.17636] [Reference Citation Analysis]
5 de Siqueira VS, Borges MM, Furtado RG, Dourado CN, da Costa RM. Artificial intelligence applied to support medical decisions for the automatic analysis of echocardiogram images: A systematic review. Artif Intell Med 2021;120:102165. [PMID: 34629153 DOI: 10.1016/j.artmed.2021.102165] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Wang S, Patel H, Miller T, Ameyaw K, Narang A, Chauhan D, Anand S, Anyanwu E, Besser SA, Kawaji K, Liu XP, Lang RM, Mor-Avi V, Patel AR. AI Based CMR Assessment of Biventricular Function: Clinical Significance of Intervendor Variability and Measurement Errors. JACC Cardiovasc Imaging 2021:S1936-878X(21)00638-0. [PMID: 34656471 DOI: 10.1016/j.jcmg.2021.08.011] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
7 Morita SX, Kusunose K, Haga A, Sata M, Hasegawa K, Raita Y, Reilly MP, Fifer MA, Maurer MS, Shimada YJ. Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy. Front Cardiovasc Med 2021;8:669860. [PMID: 34513940 DOI: 10.3389/fcvm.2021.669860] [Reference Citation Analysis]
8 Hou Y, Zhou Y, Hussain M, Budd GT, Tang WHW, Abraham J, Xu B, Shah C, Moudgil R, Popovic Z, Watson C, Cho L, Chung M, Kanj M, Kapadia S, Griffin B, Svensson L, Collier P, Cheng F. Cardiac risk stratification in cancer patients: A longitudinal patient-patient network analysis. PLoS Med 2021;18:e1003736. [PMID: 34339408 DOI: 10.1371/journal.pmed.1003736] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
9 Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. J Am Med Inform Assoc 2021;28:2050-67. [PMID: 34151987 DOI: 10.1093/jamia/ocab098] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
10 Haq IU, Haq I, Xu B. Artificial intelligence in personalized cardiovascular medicine and cardiovascular imaging. Cardiovasc Diagn Ther 2021;11:911-23. [PMID: 34295713 DOI: 10.21037/cdt.2020.03.09] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
11 Lal JC, Brown SA, Collier P, Cheng F. A retrospective analysis of cardiovascular adverse events associated with immune checkpoint inhibitors. Cardiooncology 2021;7:19. [PMID: 34049595 DOI: 10.1186/s40959-021-00106-x] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
12 Nabi W, Bansal A, Xu B. Applications of artificial intelligence and machine learning approaches in echocardiography. Echocardiography 2021;38:982-92. [PMID: 33982820 DOI: 10.1111/echo.15048] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
13 Mork C, Wei M, Jiang W, Ren J, Ran H. Aortic Annular Sizing Using Novel Software in Three-Dimensional Transesophageal Echocardiography for Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2021;11:751. [PMID: 33922239 DOI: 10.3390/diagnostics11050751] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
14 Xu B, Lo Presti Vega S, Reyaldeen R. Artificial intelligence in structural heart disease interventions - The future is near. Trends Cardiovasc Med 2021:S1050-1738(21)00028-1. [PMID: 33667645 DOI: 10.1016/j.tcm.2021.02.007] [Reference Citation Analysis]
15 Zhou Y, Hou Y, Hussain M, Brown SA, Budd T, Tang WHW, Abraham J, Xu B, Shah C, Moudgil R, Popovic Z, Cho L, Kanj M, Watson C, Griffin B, Chung MK, Kapadia S, Svensson L, Collier P, Cheng F. Machine Learning-Based Risk Assessment for Cancer Therapy-Related Cardiac Dysfunction in 4300 Longitudinal Oncology Patients. J Am Heart Assoc 2020;9:e019628. [PMID: 33241727 DOI: 10.1161/JAHA.120.019628] [Cited by in Crossref: 3] [Cited by in F6Publishing: 10] [Article Influence: 1.5] [Reference Citation Analysis]
16 Zéboulon P, Debellemanière G, Bouvet M, Gatinel D. Corneal Topography Raw Data Classification Using a Convolutional Neural Network. Am J Ophthalmol 2020;219:33-9. [PMID: 32533948 DOI: 10.1016/j.ajo.2020.06.005] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 6.0] [Reference Citation Analysis]