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ORCIDLorenzo Famiglini
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2020 – today
- 2024
[j5]Federico Cabitza
, Chiara Natali, Lorenzo Famiglini, Andrea Campagner, Valerio Caccavella, Enrico Gallazzi:
Never tell me the odds: Investigating pro-hoc explanations in medical decision making. Artif. Intell. Medicine 150: 102819 (2024)- [j4]Lorenzo Famiglini, Andrea Campagner, Marília Barandas, Giovanni Andrea La Maida, Enrico Gallazzi, Federico Cabitza:
Evidence-based XAI: An empirical approach to design more effective and explainable decision support systems. Comput. Biol. Medicine 170: 108042 (2024) - [j3]Marília Barandas, Lorenzo Famiglini, Andrea Campagner, Duarte Folgado, Raquel Simão, Federico Cabitza, Hugo Gamboa:
Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram. Inf. Fusion 101: 101978 (2024) - [c11]Federico Cabitza, Lorenzo Famiglini, Andrea Campagner, Luca Maria Sconfienza, Stefano Fusco, Valerio Caccavella, Enrico Gallazzi:
Dissimilar Similarities: Comparing Human and Statistical Similarity Evaluation in Medical AI. MDAI 2024: 187-198 - 2023
- [j2]Andrea Campagner, Lorenzo Famiglini, Anna Carobene, Federico Cabitza:
Everything is varied: The surprising impact of instantial variation on ML reliability. Appl. Soft Comput. 146: 110644 (2023) - [j1]Duarte Folgado, Marília Barandas, Lorenzo Famiglini, Ricardo Santos, Federico Cabitza, Hugo Gamboa:
Explainability meets uncertainty quantification: Insights from feature-based model fusion on multimodal time series. Inf. Fusion 100: 101955 (2023) - [c10]Andrea Campagner, Lorenzo Famiglini, Beatrice Arosio, Paolo Rossi, Giorgio Annoni, Federico Cabitza:
Biomarkers for mixed dementia: a hard bone to bite? Preliminary analyses and promising results for a debated topic. AIxAS@AI*IA 2023: 136-143 - [c9]Federico Cabitza, Andrea Campagner, Lorenzo Famiglini, Chiara Natali, Valerio Caccavella, Enrico Gallazzi:
Let Me Think! Investigating the Effect of Explanations Feeding Doubts About the AI Advice. CD-MAKE 2023: 155-169 - [c8]Lorenzo Famiglini, Andrea Campagner, Federico Cabitza:
Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use. ECAI 2023: 645-652 - [c7]Chiara Natali, Lorenzo Famiglini, Andrea Campagner, Giovanni Andrea La Maida, Enrico Gallazzi, Federico Cabitza:
Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making. xAI (1) 2023: 618-629 - 2022
- [c6]Federico Cabitza, Andrea Campagner, Lorenzo Famiglini, Enrico Gallazzi, Giovanni Andrea La Maida:
Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning. CD-MAKE 2022: 31-50 - [c5]Federico Cabitza, Andrea Campagner, Lorenzo Famiglini:
Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models' Calibration. CD-MAKE 2022: 82-99 - [c4]Andrea Campagner, Lorenzo Famiglini, Federico Cabitza:
Re-calibrating Machine Learning Models Using Confidence Interval Bounds. MDAI 2022: 132-142 - [c3]Andrea Campagner, Lorenzo Famiglini, Federico Cabitza:
A Confidence Interval-Based Method for Classifier Re-Calibration. MIE 2022: 127-128 - [i1]Andrea Campagner, Lorenzo Famiglini, Anna Carobene, Federico Cabitza:
Everything is Varied: The Surprising Impact of Individual Variation on ML Robustness in Medicine. CoRR abs/2210.04555 (2022) - 2021
- [c2]Lorenzo Famiglini, Giorgio Bini, Anna Carobene, Andrea Campagner, Federico Cabitza:
Prediction of ICU admission for COVID-19 patients: a Machine Learning approach based on Complete Blood Count data. CBMS 2021: 160-165 - [c1]Lorenzo Famiglini, Elisabetta Fersini, Paolo Rosso:
On the Generalization of Figurative Language Detection: The Case of Irony and Sarcasm. NLDB 2021: 178-186
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