BESOZZI DANIELA

Torlasco, C., Papetti, D., Castelletti, S., Sabatini, M., Muscogiuri, G., Badano, L., et al. (2023). Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation. In EACVI 2023 Abstract (pp.153-154). Oxford University Press [10.1093/ehjci/jead119.103]. Dettaglio

La Vacca, G., Della torre, S., Cavallotto, G., Besozzi, D., Gervasi, M., Nobile, M., et al. (2023). Advantages of GPU-accelerated approach for solving the Parker equation in the heliosphere. In 38th International Cosmic Ray Conference (pp.1-8). Sissa Medialab srl [10.22323/1.444.1290]. Dettaglio

Coelho, V., Papetti, D., Tangherloni, A., Cazzaniga, P., Besozzi, D., Nobile, M. (2023). The Domination Game: Dilating Bubbles to Fill Up Pareto Fronts. In 2023 IEEE Congress on Evolutionary Computation, CEC 2023 (pp.1-8). Institute of Electrical and Electronics Engineers Inc. [10.1109/CEC53210.2023.10253982]. Dettaglio

Papetti, D., Spolaor, S., Nazari, I., Tirelli, A., Leonardi, T., Caprioli, C., et al. (2023). Barcode demultiplexing of nanopore sequencing raw signals by unsupervised machine learning. FRONTIERS IN BIOINFORMATICS, 3 [10.3389/fbinf.2023.1067113]. Dettaglio

Botta, C., Perez, C., Larrayoz, M., Puig, N., Cedena, M., Termini, R., et al. (2023). Large T cell clones expressing immune checkpoints increase during multiple myeloma evolution and predict treatment resistance. NATURE COMMUNICATIONS, 14(1) [10.1038/s41467-023-41562-6]. Dettaglio