BESOZZI DANIELA

Barreca, M., Mariani, M., Dugo, M., Galbardi, B., Valagussa, P., Besozzi, D., et al. (2024). Tumour ecosystem and molecular dynamics in clinical triple-negative breast cancer depend on the chemotherapy regimen. Intervento presentato a: IMMUNO-models Second Annual Conference: From Pre-clinical Models to the Search for Biomarkers in Immuno-Oncology, Bratislava, Slovacchia. Detail

Barreca, M., Mariani, M., Dugo, M., Galbardi, B., Valagussa, P., Besozzi, D., et al. (2024). Tumour ecosystem and molecular dynamics in clinical triple-negative breast cancer depend on the chemotherapy regimen. Intervento presentato a: Mario Negri: PhD Student Meeting, Milano, Italia. Detail

Barreca, M., Mariani, M., Dugo, M., Galbardi, B., Valagussa, P., Besozzi, D., et al. (2024). Tumour ecosystem and molecular dynamics in clinical triple-negative breast cancer depend on the chemotherapy regimen. Intervento presentato a: EACR - European Association for Cancer Research - Cancer Genomics, Multiomics and Computational Biology, Bergamo, Italia. Detail

Locatelli, M., Cerioli, R., Besozzi, D., Hommersom, A., Stella, F. (2024). Reinforcement Learning and Fuzzy Logic Modelling for Personalized Dynamic Treatment. In Proceedings of the 3rd AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2024)
co-located with the 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2024) (pp.116-129). CEUR-WS. Detail

L'Imperio, V., Coelho, V., Cazzaniga, G., Papetti, D., Del Carro, F., Capitoli, G., et al. (2024). Machine learning streamlines the morphometric characterization and multi-class segmentation of nuclei in different follicular thyroid lesions: everything in a NUTSHELL. MODERN PATHOLOGY, 37(12 (December 2024)) [10.1016/j.modpat.2024.100608]. Detail