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Laura Palagi

Showing results (1-10 of 11) with videos related to

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IEEE Transactions on Neural Networks|May 14, 2009
A convergent hybrid decomposition algorithm model for SVM trainingStefano Lucidi, Laura Palagi, Arnaldo Risi, et al.
Life (Basel, Switzerland)|February 10, 2021
Machine Learning Use for Prognostic Purposes in Multiple SclerosisRuggiero Seccia, Silvia Romano, Marco Salvetti, et al.
Plos One|December 23, 2021
Supervised and unsupervised learning to classify scoliosis and healthy subjects based on non-invasive rasterstereography analysisTommaso Colombo, Massimiliano Mangone, Francesco Agostini, et al.
Genes|November 27, 2021
MOSES: A New Approach to Integrate Interactome Topology and Functional Features for Disease Gene PredictionManuela Petti, Lorenzo Farina, Federico Francone, et al.
Bioinformatics (Oxford, England)|May 22, 2024
Incorporating temporal dynamics of mutations to enhance the prediction capability of antiretroviral therapy's outcome for HIV-1Giulia Di Teodoro, Martin Pirkl, Francesca Incardona, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|January 14, 2025
A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1Giulia Di Teodoro, Federico Siciliano, Valerio Guarrasi, et al.
Plos One|March 21, 2020
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosisRuggiero Seccia, Daniele Gammelli, Fabio Dominici, et al.
Healthcare (Basel, Switzerland)|September 28, 2023
Deep Neural Network Regression to Assist Non-Invasive Diagnosis of Portal HypertensionFederico Baldisseri, Andrea Wrona, Danilo Menegatti, et al.
Data in Brief|April 8, 2020
Data of patients undergoing rehabilitation programsRuggiero Seccia, Marco Boresta, Federico Fusco, et al.
International Journal of Environmental Research and Public Health|April 28, 2023
The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological PatientsValter Santilli, Massimiliano Mangone, Anxhelo Diko, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
IEEE Transactions on Neural Networks|May 14, 2009
A convergent hybrid decomposition algorithm model for SVM trainingStefano Lucidi, Laura Palagi, Arnaldo Risi, et al.
Life (Basel, Switzerland)|February 10, 2021
Machine Learning Use for Prognostic Purposes in Multiple SclerosisRuggiero Seccia, Silvia Romano, Marco Salvetti, et al.
Plos One|December 23, 2021
Supervised and unsupervised learning to classify scoliosis and healthy subjects based on non-invasive rasterstereography analysisTommaso Colombo, Massimiliano Mangone, Francesco Agostini, et al.
Genes|November 27, 2021
MOSES: A New Approach to Integrate Interactome Topology and Functional Features for Disease Gene PredictionManuela Petti, Lorenzo Farina, Federico Francone, et al.
Bioinformatics (Oxford, England)|May 22, 2024
Incorporating temporal dynamics of mutations to enhance the prediction capability of antiretroviral therapy's outcome for HIV-1Giulia Di Teodoro, Martin Pirkl, Francesca Incardona, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|January 14, 2025
A graph neural network-based model with out-of-distribution robustness for enhancing antiretroviral therapy outcome prediction for HIV-1Giulia Di Teodoro, Federico Siciliano, Valerio Guarrasi, et al.
Plos One|March 21, 2020
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosisRuggiero Seccia, Daniele Gammelli, Fabio Dominici, et al.
Healthcare (Basel, Switzerland)|September 28, 2023
Deep Neural Network Regression to Assist Non-Invasive Diagnosis of Portal HypertensionFederico Baldisseri, Andrea Wrona, Danilo Menegatti, et al.
Data in Brief|April 8, 2020
Data of patients undergoing rehabilitation programsRuggiero Seccia, Marco Boresta, Federico Fusco, et al.
International Journal of Environmental Research and Public Health|April 28, 2023
The Use of Machine Learning for Inferencing the Effectiveness of a Rehabilitation Program for Orthopedic and Neurological PatientsValter Santilli, Massimiliano Mangone, Anxhelo Diko, et al.
Pageof 2