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Aquino GJ, Chamberlin J, Mercer M, et al. Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes. J Cardiovasc Comput Tomogr. 2021;doi: 10.1016/j.jcct.2021.12.005.
Aquino, G. J., Chamberlin, J., Mercer, M., Kocher, M., Kabakus, I., Akkaya, S., Fiegel, M., Brady, S., Leaphart, N., Dippre, A., Giovagnoli, V., Yacoub, B., Jacob, A., Gulsun, M. A., Sahbaee, P., Sharma, P., Waltz, J., Schoepf, U. J., Baruah, D., Emrich, T., Zimmerman, S., Field, M. E., Agha, A. M., & Burt, J. R. (2021). Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes. Journal of cardiovascular computed tomography, . https://doi.org/10.1016/j.jcct.2021.12.005
Aquino, Gilberto J, et al. "Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes." Journal of cardiovascular computed tomography vol. (2021). doi: https://doi.org/10.1016/j.jcct.2021.12.005
Aquino GJ, Chamberlin J, Mercer M, Kocher M, Kabakus I, Akkaya S, Fiegel M, Brady S, Leaphart N, Dippre A, Giovagnoli V, Yacoub B, Jacob A, Gulsun MA, Sahbaee P, Sharma P, Waltz J, Schoepf UJ, Baruah D, Emrich T, Zimmerman S, Field ME, Agha AM, Burt JR. Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes. J Cardiovasc Comput Tomogr. 2021 Dec 17; doi: 10.1016/j.jcct.2021.12.005. Epub 2021 Dec 17. PMID: 34969636.
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