PAPETTI DANIELE MARIA

Facchinetti, F., L'Imperio, V., Piga, I., Papetti, D., Capitoli, G. (2026). Boosting thyroid nodule diagnosis through ultrasound and molecular imaging integration with unsupervised learning. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 16(6), 1-9 [10.21037/qims-2025-1125]. Dettaglio

Coelho, V., Monza, N., Porto, N., Capitoli, G., L'Imperio, V., Papetti, D., et al. (2026). Improving the Annotation for Spatial Proteomics: A Computational Approach to Enhance Molecular Characterization of Thyroid Nodules. JOURNAL OF PROTEOME RESEARCH, 25(2), 1152-1159 [10.1021/acs.jproteome.5c00432]. Dettaglio

Papetti, D., Nobile, M., Grazioso, M., Cazzaniga, P., Vanneschi, L., Besozzi, D. (2026). HyCAPS: A Settings-Free Optimization Heuristics Integrating Evolutionary Computation and Swarm Intelligence. In Applications of Evolutionary Computation 29th European Conference, EvoApplications 2026, Held as Part of EvoStar 2026, Toulouse, France, April 8–10, 2026, Proceedings, Part II (pp.375-390) [10.1007/978-3-032-23607-4_23]. Dettaglio

Marino, M., Papetti, D., Besozzi, D., Nobile, M. (2026). Local manipulations of the fitness landscape mitigate stall in particle swarm optimization. APPLIED SOFT COMPUTING, 186(Part D, January 2026) [10.1016/j.asoc.2025.114197]. Dettaglio

Bacciu, L., Urso, M., Coelho, V., Cazzaniga, G., Pincelli, A., Garancini, M., et al. (2025). MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological Images. ENDOCRINE PATHOLOGY, 36(1) [10.1007/s12022-025-09877-w]. Dettaglio