FAMIGLINI LORENZO
Publications
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
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
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
Cabitza, F., Campagner, A., Famiglini, L., Natali, C., Caccavella, V., Gallazzi, E. (2023). Let Me Think! Investigating the Effect of Explanations Feeding Doubts About the AI Advice. In Machine Learning and Knowledge Extraction
7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023, Benevento, Italy, August 29 – September 1, 2023, Proceedings (pp.155-169). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-031-40837-3_10]. Detail