BESOZZI DANIELA

Barreca, M., Dugo, M., Galbardi, B., Győrffy, B., Frassoldati, A., Zambetti, M., et al. (2024). Development and validation of a gene expression-based Breast Cancer Purity Score. NPJ PRECISION ONCOLOGY, 8(1) [10.1038/s41698-024-00730-7]. Detail

Della Torre, S., Cavallotto, G., Besozzi, D., Gervasi, M., La Vacca, G., Nobile, M., et al. (2024). 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]. 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

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