Sfoglia per Autore
Prediction of late radiotherapy toxicity in prostate cancer patients via joint analysis of SNPs sequences
2020-01-01 Franco, Nicola Rares; Massi, Michela Carlotta; Ieva, Francesca; Paganoni, Anna Maria; Manzoni, Andrea; Zunino, Paolo; Rancati, Tiziana; West, Catharine
Deep Sparse Autoencoder-based Feature Selection for SNPs validation in Prostate Cancer Radiogenomics
2020-01-01 Massi, M. C.; Ieva, F.; Paganoni, A.; Manzoni, A.; Zunino, P.; Franco, N. R.; Rancati, T.; West, C.
A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort
2020-01-01 Massi, MICHELA CARLOTTA; Gasperoni, Francesca; Ieva, Francesca; Paganoni, ANNA MARIA; Zunino, Paolo; Manzoni, Andrea; Franco, NICOLA RARES; Veldeman, Liv; Ost, Piet; Fonteyne, Val('(e))rie; Talbot, Christopher J.; Rattay, Tim; Webb, Adam; Symonds, Paul R.; Johnson, Kerstie; Lambrecht, Maarten; Haustermans, Karin; De Meerleer, Gert; de Ruysscher, Dirk; Vanneste, Ben; Van Limbergen, Evert; Choudhury, Ananya; Elliott, Rebecca M.; Sperk, Elena; Herskind, Carsten; Veldwijk, Marlon R.; Avuzzi, Barbara; Giandini, Tommaso; Valdagni, Riccardo; Cicchetti, Alessandro; Azria, David; Farcy Jacquet, Marie-Pierre; Rosenstein, Barry S.; Stock, Richard G.; Collado, Kayla; Vega, Ana; El('(i))as Aguado-Barrera, Miguel; Calvo, Patricia; Dunning, Alison M.; Fachal, Laura; Kerns, Sarah L.; Payne, Debbie; Chang-Claude, Jenny; Seibold, Petra; West, Catharine M. L.; Rancati, Tiziana
Interpretability and interaction learning for logistic regression models
2021-01-01 Franco, N. R.; Massi, M. C.; Ieva, F.; Paganoni, A. M.
Uncertainty Quantification for Parameter dependent Partial Differential Equations using Deep Neural Networks
2021-01-01 Franco, N.; Manzoni, A.; Zunino, P.
PH-0656 Prediction of toxicity after prostate cancer RT: the value of a SNP-interaction polygenic risk score
2021-01-01 Rancati, T.; Massi, M.; Franco, N.; Avuzzi, B.; Azria, D.; Choudhury, A.; Cicchetti, A.; Dirk, D. R.; Dunning, A.; Elliott, R.; Ieva, F.; Kerns, S.; Lambrecht, M.; Manzoni, A.; Paganoni, A.; Rosenstein, B.; Seibold, P.; Sperk, E.; Talbot, C.; Vega, A.; Veldeman, L.; Zunino, P.; Webb, A.; Chang-Claude, J.; West, C.
Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity
2021-01-01 Franco, Nicola Rares; Massi, Michela Carlotta; Ieva, Francesca; Manzoni, Andrea; Paganoni, Anna Maria; Zunino, Paolo; Veldeman, Liv; Ost, Piet; Fonteyne, Valérie; Talbot, Christopher J; Rattay, Tim; Webb, Adam; Johnson, Kerstie; Lambrecht, Maarten; Haustermans, Karin; De Meerleer, Gert; de Ruysscher, Dirk; Vanneste, Ben; Van Limbergen, Evert; Choudhury, Ananya; Elliott, Rebecca M; Sperk, Elena; Veldwijk, Marlon; Herskind, Carsten; Avuzzi, Barbara; Noris Chiorda, Barbara; Valdagni, Riccardo; Azria, David; Farcy-Jacquet, Marie-Pierre; Brengues, Muriel; Rosenstein, Barry S; Stock, Richard G; Vega, Ana; Elías Aguado-Barrera, Miguel; Sosa-Fajardo, Paloma; Dunning, Alison M; Fachal, Laura; Kerns, Sarah L; Payne, Debbie; Chang-Claude, Jenny; Seibold, Petra; Ml West, Catharine; Rancati, Tiziana
Deep learning-based surrogate models for parametrized PDEs: Handling geometric variability through graph neural networks
2023-01-01 Franco, Nicola Rares; Fresca, Stefania; Tombari, Filippo; Manzoni, Andrea
Learning high-order interactions for polygenic risk prediction
2023-01-01 Massi, M. C.; Franco, N. R.; Manzoni, A.; Paganoni, A. M.; Park, H. A.; Hoffmeister, M.; Brenner, H.; Chang-Claude, J.; Ieva, F.; Zunino, P.
Approximation bounds for convolutional neural networks in operator learning
2023-01-01 Franco, Nicola Rares; Fresca, Stefania; Manzoni, Andrea; Zunino, Paolo
Mesh-Informed Neural Networks for Operator Learning in Finite Element Spaces
2023-01-01 Franco, N. R.; Manzoni, A.; Zunino, P.
A deep learning approach to Reduced Order Modelling of parameter dependent partial differential equations
2023-01-01 Franco, Nicola; Manzoni, Andrea; Zunino, Paolo
Nonlinear model order reduction for problems with microstructure using mesh informed neural networks
2024-01-01 Vitullo, P; Colombo, A; Franco, Nr; Manzoni, A; Zunino, P
Deep learning enhanced cost-aware multi-fidelity uncertainty quantification of a computational model for radiotherapy
2024-01-01 Vitullo, Piermario; Franco, Nicola Rares; Zunino, Paolo
Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition
2024-01-01 Brivio, Simone; Fresca, Stefania; Franco, Nicola Rares; Manzoni, Andrea
On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields
2024-01-01 Franco, Nicola Rares; Fraulin, Daniel; Manzoni, Andrea; Zunino, Paolo
A practical existence theorem for reduced order models based on convolutional autoencoders
2024-01-01 Franco, Nicola Rares; Brugiapaglia, Simone
Neural network solvers for parametrized elasticity problems that conserve linear and angular momentum
2025-01-01 Boon, Wietse M.; Franco, Nicola R.; Fumagalli, Alessio
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