FAMIGLINI LORENZO

Role
PhD Student  

Publications

  • Famiglini, L., Campagner, A., Barandas, M., La Maida, G., Gallazzi, E., Cabitza, F. (2024). Evidence-based XAI: An empirical approach to design more effective and explainable decision support systems. COMPUTERS IN BIOLOGY AND MEDICINE, 170(March 2024) [10.1016/j.compbiomed.2024.108042]. Detail

  • Cabitza, F., Natali, C., Famiglini, L., Campagner, A., Caccavella, V., Gallazzi, E. (2024). Never tell me the odds: Investigating pro-hoc explanations in medical decision making. ARTIFICIAL INTELLIGENCE IN MEDICINE, 150(April 2024), 1-11 [10.1016/j.artmed.2024.102819]. Detail

  • Barandas, M., Famiglini, L., Campagner, A., Folgado, D., Simao, R., Cabitza, F., et al. (2024). Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram. INFORMATION FUSION, 101(January 2024) [10.1016/j.inffus.2023.101978]. Detail

  • Campagner, A., Famiglini, L., Carobene, A., Cabitza, F. (2023). Everything is varied: The surprising impact of instantial variation on ML reliability. APPLIED SOFT COMPUTING, 146(October 2023) [10.1016/j.asoc.2023.110644]. Detail

  • Famiglini, L., Campagner, A., Cabitza, F. (2023). Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use. In ECAI 2023. 26th European Conference on Artificial Intelligence. September 30–October 4, 2023, Kraków, Poland. Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023). Proceedings (pp.645-652). IOS Press BV [10.3233/FAIA230327]. Detail

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