Search Results - Gauriau, R

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  1. 1
    154 Can we improve the accuracy and reproducibility of left ventricular ejection fraction from 2D echocardiography using artificial intelligence? A validation against cardiac magnetic resonance

    154 Can we improve the accuracy and reproducibility of left ventricular ejection fraction from 2D echocardiography using artificial intelligence? A validation against cardiac magne... by Popoff, A, Langet, H, Piro, P, Ropert, C, Allain, P, Gauriau, R, Pizaine, G, De Craene, M, Gerber, B, Saloux, E

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  2. 2
    Development and clinical application of a deep learning model to identify acute infarct on magnetic resonance imaging

    Development and clinical application of a deep learning model to identify acute infarct on magnetic resonance imaging by Bridge, Christopher P., Bizzo, Bernardo C., Hillis, James M., Chin, John K., Comeau, Donnella S., Gauriau, Romane, Macruz, Fabiola, Pawar, Jayashri, Noro, Flavia T. C., Sharaf, Elshaimaa, Straus Takahashi, Marcelo, Wright, Bradley, Kalafut, John F., Andriole, Katherine P., Pomerantz, Stuart R., Pedemonte, Stefano, González, R. Gilberto

    Published in Scientific reports
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  3. 3
    Head CT deep learning model is highly accurate for early infarct estimation

    Head CT deep learning model is highly accurate for early infarct estimation by Gauriau, Romane, Bizzo, Bernardo C., Comeau, Donnella S., Hillis, James M., Bridge, Christopher P., Chin, John K., Pawar, Jayashri, Pourvaziri, Ali, Sesic, Ivana, Sharaf, Elshaimaa, Cao, Jinjin, Noro, Flavia T. C., Wiggins, Walter F., Caton, M. Travis, Kitamura, Felipe, Dreyer, Keith J., Kalafut, John F., Andriole, Katherine P., Pomerantz, Stuart R., Gonzalez, Ramon G., Lev, Michael H.

    Published in Scientific reports
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  4. 4
    A method to evaluate the degree of bleaching of IRSL signals in feldspar: The 3ET method

    A method to evaluate the degree of bleaching of IRSL signals in feldspar: The 3ET method by Ivester, A.H., Rhodes, E.J., Dolan, J.F., Van Dissen, R.J., Gauriau, J., Little, T., McGill, S.F., Tuckett, P.A.

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  5. 5
    A Deep Learning–based Model for Detecting Abnormalities on Brain MR Images for Triaging: Preliminary Results from a Multisite Experience

    A Deep Learning–based Model for Detecting Abnormalities on Brain MR Images for Triaging: Preliminary Results from a Multisite Experience by Gauriau, Romane, Bizzo, Bernardo C., Kitamura, Felipe C., Landi Junior, Osvaldo, Ferraciolli, Suely F., Macruz, Fabiola B. C., Sanchez, Tiago A., Garcia, Marcio R. T., Vedolin, Leonardo M., Domingues, Romeu C., Gasparetto, Emerson L., Andriole, Katherine P.

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  6. 6
    Quality indicators for colorectal cancer surgery and care according to patient-, tumor-, and hospital-related factors

    Quality indicators for colorectal cancer surgery and care according to patient-, tumor-, and hospital-related factors by Mathoulin-Pélissier, Simone, Bécouarn, Yves, Belleannée, Geneviève, Pinon, Elodie, Jaffré, Anne, Coureau, Gaëlle, Auby, Dominique, Renaud-Salis, Jean-Louis, Rullier, Eric

    Published in BMC cancer
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  7. 7
    P104 - Sténose du pylore compliquée d’un abcès de paroi à streptocoque B chez un nouveau né de un mois

    P104 - Sténose du pylore compliquée d’un abcès de paroi à streptocoque B chez un nouveau né de un mois by Greteau, S., Robert, V., Bauvin, I., Kerouanton, A., Andriantsoa, R., Parent, Y., Gauriau, L., Doireau, V., Guerin, B., Choulot, J.J.

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