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Alessandra Bertoldo

Showing results (11-20 of 166) with videos related to

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The AAPS Journal|August 13, 2015
Visual Predictive Check in Models with Time-Varying Input FunctionAnna Largajolli, Alessandra Bertoldo, Marco Campioni, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 7, 2016
Modelling arterial input functions in positron emission tomography dynamic studiesMatteo Tonietto, Gaia Rizzo, Mattia Veronese, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 24, 2009
Glucose Minimal Model population analysis: likelihood function profiling via Monte Carlo samplingPaolo Denti, Paolo Vicini, Alessandra Bertoldo, et al.
The Lancet. Neurology|June 14, 2024
Glioblastoma and brain connectivity: the need for a paradigm shiftAlessandro Salvalaggio, Lorenzo Pini, Alessandra Bertoldo, et al.
American Journal of Physiology. Endocrinology and Metabolism|January 28, 2010
IVGTT glucose minimal model covariate selection by nonlinear mixed-effects approachPaolo Denti, Alessandra Bertoldo, Paolo Vicini, et al.
Computer Methods and Programs in Biomedicine|April 5, 2011
Automatic selection of arterial input function on dynamic contrast-enhanced MR imagesDenis Peruzzo, Alessandra Bertoldo, Francesca Zanderigo, et al.
IEEE Transactions on Bio-Medical Engineering|April 22, 2009
Nonlinear mixed effects to improve glucose minimal model parameter estimation: a simulation study in intensive and sparse samplingPaolo Denti, Alessandra Bertoldo, Paolo Vicini, et al.
Magnetic Resonance in Medicine|January 11, 2017
Stable spline deconvolution for dynamic susceptibility contrast MRIDenis Peruzzo, Marco Castellaro, Gianluigi Pillonetto, et al.
Critical Reviews in Oncology/Hematology|July 11, 2024
Perioperative imaging predictors of tumor progression and pseudoprogression: A systematic reviewGiovanni Librizzi, Giuseppe Lombardi, Alessandra Bertoldo, et al.
Computer Methods and Programs in Biomedicine|April 25, 2013
SAKE: a new quantification tool for positron emission tomography studiesMattia Veronese, Gaia Rizzo, Federico E Turkheimer, et al.
Pageof 17

Showing results (11-20 of 166) with videos related to

Sort By:
Pageof 17
The AAPS Journal|August 13, 2015
Visual Predictive Check in Models with Time-Varying Input FunctionAnna Largajolli, Alessandra Bertoldo, Marco Campioni, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 7, 2016
Modelling arterial input functions in positron emission tomography dynamic studiesMatteo Tonietto, Gaia Rizzo, Mattia Veronese, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|January 24, 2009
Glucose Minimal Model population analysis: likelihood function profiling via Monte Carlo samplingPaolo Denti, Paolo Vicini, Alessandra Bertoldo, et al.
The Lancet. Neurology|June 14, 2024
Glioblastoma and brain connectivity: the need for a paradigm shiftAlessandro Salvalaggio, Lorenzo Pini, Alessandra Bertoldo, et al.
American Journal of Physiology. Endocrinology and Metabolism|January 28, 2010
IVGTT glucose minimal model covariate selection by nonlinear mixed-effects approachPaolo Denti, Alessandra Bertoldo, Paolo Vicini, et al.
Computer Methods and Programs in Biomedicine|April 5, 2011
Automatic selection of arterial input function on dynamic contrast-enhanced MR imagesDenis Peruzzo, Alessandra Bertoldo, Francesca Zanderigo, et al.
IEEE Transactions on Bio-Medical Engineering|April 22, 2009
Nonlinear mixed effects to improve glucose minimal model parameter estimation: a simulation study in intensive and sparse samplingPaolo Denti, Alessandra Bertoldo, Paolo Vicini, et al.
Magnetic Resonance in Medicine|January 11, 2017
Stable spline deconvolution for dynamic susceptibility contrast MRIDenis Peruzzo, Marco Castellaro, Gianluigi Pillonetto, et al.
Critical Reviews in Oncology/Hematology|July 11, 2024
Perioperative imaging predictors of tumor progression and pseudoprogression: A systematic reviewGiovanni Librizzi, Giuseppe Lombardi, Alessandra Bertoldo, et al.
Computer Methods and Programs in Biomedicine|April 25, 2013
SAKE: a new quantification tool for positron emission tomography studiesMattia Veronese, Gaia Rizzo, Federico E Turkheimer, et al.
Pageof 17