Andrea Campagner

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 78

Top Topics

Feature Selection

Aggregation Operators

Weakly Supervised

Top Venues

Publications

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 (2024)
Stefania Boffa, Andrea Campagner, Davide Ciucci
Partially-defined equivalence relations: Relationship with orthopartitions and connection to rough sets. Inf. Sci. 657 (2024)
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)
Federico Cabitza, Andrea Campagner, Riccardo Angius, Chiara Natali, Carlo Reverberi
AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making. CHI (2023)
Federico Cabitza, Andrea Campagner, Luca Ronzio, Matteo Cameli, Giulia Elena Mandoli, Maria Concetta Pastore, Luca Maria Sconfienza, Duarte Folgado, Marília Barandas, Hugo Gamboa
Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis. Artif. Intell. Medicine 138 (2023)
David Schneeberger, Richard Röttger, Federico Cabitza, Andrea Campagner, Markus Plass, Heimo Müller, Andreas Holzinger
The Tower of Babel in Explainable Artificial Intelligence (XAI). CD-MAKE (2023)
Peter Kieseberg, Edgar R. Weippl, A Min Tjoa, Federico Cabitza, Andrea Campagner, Andreas Holzinger
Controllable AI - An Alternative to Trustworthiness in Complex AI Systems? CD-MAKE (2023)
Andrea Campagner, Riccardo Angius, Federico Cabitza
A Question of Trust: Old and New Metrics for the Reliable Assessment of Trustworthy AI. HEALTHINF (2023)
Andrea Campagner, Davide Ciucci, Federico Cabitza
Aggregation models in ensemble learning: A large-scale comparison. Inf. Fusion 90 (2023)
Andrea Campagner, Davide Ciucci, Thierry Denoeux
A general framework for evaluating and comparing soft clusterings. Inf. Sci. 623 (2023)
Federico Cabitza, Andrea Campagner, Gianclaudio Malgieri, Chiara Natali, David Schneeberger, Karl Stöger, Andreas Holzinger
Quod erat demonstrandum? - Towards a typology of the concept of explanation for the design of explainable AI. Expert Syst. Appl. 213 (Part) (2023)
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)
Federico Cabitza, Andrea Campagner, Chiara Natali, Enea Parimbelli, Luca Ronzio, Matteo Cameli
Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting. Mach. Learn. Knowl. Extr. 5 (1) (2023)
Federico Cabitza, Andrea Campagner, Valerio Basile
Toward a Perspectivist Turn in Ground Truthing for Predictive Computing. AAAI (2023)
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)
Stefania Boffa, Andrea Campagner, Davide Ciucci, Yiyu Yao
Aggregation Operators on Shadowed Sets Deriving from Conditional Events and Consensus Operators. IJCRS (2023)
Andrea Campagner, Davide Ciucci, Thierry Denoeux
A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering. Int. J. Approx. Reason. 162 (2023)
Frida Milella, Chiara Natali, Teresa Scantamburlo, Andrea Campagner, Federico Cabitza
The Impact of Gender and Personality in Human-AI Teaming: The Case of Collaborative Question Answering. INTERACT (2) (2023)
Andrea Campagner
Credal Learning: Weakly Supervised Learning from Credal Sets. ECAI (2023)
Lorenzo Famiglini, Andrea Campagner, Federico Cabitza
Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use. ECAI (2023)
Andrea Campagner, Lorenzo Famiglini, Anna Carobene, Federico Cabitza
Everything is varied: The surprising impact of instantial variation on ML reliability. Appl. Soft Comput. 146 (2023)
Federico Cabitza, Andrea Campagner, Chiara Natali
Demo: Decision Support System Quality Assessment Tool. CHItaly (2023)
Andrea Campagner, Lorenzo Famiglini, Federico Cabitza
A Confidence Interval-Based Method for Classifier Re-Calibration. MIE (2022)
Federico Cabitza, Andrea Campagner, Lorenzo Famiglini
Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models' Calibration. CD-MAKE (2022)
Davide Ciucci, Stefania Boffa, Andrea Campagner
Orthopartitions in Knowledge Representation and Machine Learning. IJCRS (2022)
Federico Cabitza, Matteo Cameli, Andrea Campagner, Chiara Natali, Luca Ronzio
Painting the black box white: experimental findings from applying XAI to an ECG reading setting. CoRR (2022)
Andrea Campagner, Davide Ciucci, Valentina Dorigatti
Uncertainty representation in dynamical systems using rough set theory. Theor. Comput. Sci. 908 (2022)
Andrea Campagner, Davide Ciucci, Thierry Denoeux
Belief functions and rough sets: Survey and new insights. Int. J. Approx. Reason. 143 (2022)
Andrea Campagner, Davide Ciucci
Rough-set Based Genetic Algorithms for Weakly Supervised Feature Selection. IPMU (2) (2022)
Nuno Bento, Joana Rebelo, Marília Barandas, André V. Carreiro, Andrea Campagner, Federico Cabitza, Hugo Gamboa
Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition. Sensors 22 (19) (2022)
Andrea Campagner, Davide Ciucci, Thierry Denoeux
A Distributional Approach for Soft Clustering Comparison and Evaluation. BELIEF (2022)
Andrea Campagner, Federico Sternini, Federico Cabitza
Decisions are not all equal - Introducing a utility metric based on case-wise raters' perceptions. Comput. Methods Programs Biomed. 221 (2022)
Federico Cabitza, Andrea Campagner, Martina Mattioli
The unbearable (technical) unreliability of automated facial emotion recognition. Big Data Soc. 9 (2) (2022)
Federico Cabitza, Andrea Campagner, Enrico Conte
Comparative Assessment of Two Data Visualizations to Communicate Medical Test Results Online. VISIGRAPP (3: IVAPP) (2022)
Andrea Campagner, Davide Ciucci, Thierry Denoeux
A Distributional Approach for Soft Clustering Comparison and Evaluation. CoRR (2022)
Andrea Campagner, Julian Lienen, Eyke Hüllermeier, Davide Ciucci
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning. IJCRS (2022)
Stefania Boffa, Andrea Campagner, Davide Ciucci, Yiyu Yao
Aggregation operators on shadowed sets. Inf. Sci. 595 (2022)
Andrea Campagner, Davide Ciucci
Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision. FedCSIS (2022)
Andrea Campagner, Lorenzo Famiglini, Federico Cabitza
Re-calibrating Machine Learning Models Using Confidence Interval Bounds. MDAI (2022)
Andrea Campagner, Lorenzo Famiglini, Anna Carobene, Federico Cabitza
Everything is Varied: The Surprising Impact of Individual Variation on ML Robustness in Medicine. CoRR (2022)
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)
Andrea Campagner, Davide Ciucci
Feature Selection and Disambiguation in Learning from Fuzzy Labels Using Rough Sets. IJCRS (2021)
Federico Cabitza, Andrea Campagner, Felipe Soares, Luis García de Guadiana-Romualdo, Feyissa Challa, Adela Sulejmani, Michela Seghezzi, Anna Carobene
The importance of being external. methodological insights for the external validation of machine learning models in medicine. Comput. Methods Programs Biomed. 208 (2021)
Andrea Campagner, Anna Carobene, Federico Cabitza
External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count. Health Inf. Sci. Syst. 9 (1) (2021)
Federico Cabitza, Andrea Campagner, Valentina Cavosi
Assessing the impact of medical AI: a survey of physicians' perceptions. ICMHI (2021)
Valerio Basile, Federico Cabitza, Andrea Campagner, Michael Fell
Toward a Perspectivist Turn in Ground Truthing for Predictive Computing. CoRR (2021)
Inês Neves, Duarte Folgado, Sara Santos, Marília Barandas, Andrea Campagner, Luca Ronzio, Federico Cabitza, Hugo Gamboa
Interpretable heartbeat classification using local model-agnostic explanations on ECGs. Comput. Biol. Medicine 133 (2021)
Andrea Campagner, Enrico Conte, Federico Cabitza
Weighted Utility: A Utility Metric Based on the Case-Wise Raters' Perceptions. CD-MAKE (2021)
Andrea Campagner, Davide Ciucci, Eyke Hüllermeier
Rough set-based feature selection for weakly labeled data. Int. J. Approx. Reason. 136 (2021)
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)
Andrea Campagner, Federico Cabitza, Pedro Berjano, Davide Ciucci
Three-way decision and conformal prediction: Isomorphisms, differences and theoretical properties of cautious learning approaches. Inf. Sci. 579 (2021)
Andrea Campagner, Davide Ciucci, Carl-Magnus Svensson, Marc Thilo Figge, Federico Cabitza
Ground truthing from multi-rater labeling with three-way decision and possibility theory. Inf. Sci. 545 (2021)
Federico Cabitza, Andrea Campagner
The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies. Int. J. Medical Informatics 153 (2021)
Federico Cabitza, Andrea Campagner, Luca Maria Sconfienza
Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double reading. Health Inf. Sci. Syst. 9 (1) (2021)
Andrea Campagner
Learnability in "Learning from Fuzzy Labels". FUZZ-IEEE (2021)
Federico Cabitza, Andrea Campagner, Carla Simone
The need to move away from agential-AI: Empirical investigations, useful concepts and open issues. Int. J. Hum. Comput. Stud. 155 (2021)
Andrea Campagner, Luca Maria Sconfienza, Federico Cabitza
H-Accuracy, an Alternative Metric to Assess Classification Models in Medicine. MIE (2020)
Andrea Campagner, Davide Ciucci, Valentina Dorigatti
Approximate Reaction Systems Based on Rough Set Theory. IJCRS (2020)
Andrea Seveso, Andrea Campagner, Davide Ciucci, Federico Cabitza
Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings. BMC Medical Informatics Decis. Mak. (5) (2020)
Andrea Campagner, Davide Ciucci
A Formal Learning Theory for Three-Way Clustering. SUM (2020)
Andrea Campagner, Valentina Dorigatti, Davide Ciucci
Entropy-based shadowed set approximation of intuitionistic fuzzy sets. Int. J. Intell. Syst. 35 (12) (2020)
Andrea Campagner, Davide Ciucci, Federico Cabitza
Ensemble Learning, Social Choice and Collective Intelligence - An Experimental Comparison of Aggregation Techniques. MDAI (2020)
Federico Cabitza, Andrea Campagner, Luca Maria Sconfienza
As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI. BMC Medical Informatics Decis. Mak. 20 (1) (2020)
Andrea Campagner, Davide Ciucci, Eyke Hüllermeier
Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory. IPMU (1) (2020)
Andrea Campagner, Federico Cabitza, Davide Ciucci
The three-way-in and three-way-out framework to treat and exploit ambiguity in data. Int. J. Approx. Reason. 119 (2020)
Davide Brinati, Andrea Campagner, Davide Ferrari, Massimo Locatelli, Giuseppe Banfi, Federico Cabitza
Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study. J. Medical Syst. 44 (8) (2020)
Andrea Campagner, Pedro Berjano, Claudio Lamartina, Francesco Langella, Giovanni Lombardi, Federico Cabitza
Assessment and prediction of spine surgery invasiveness with machine learning techniques. Comput. Biol. Medicine 121 (2020)
Andrea Campagner, Federico Cabitza
Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground Truth. MIE (2020)
Andrea Campagner, Federico Cabitza
Back to the Feature: A Neural-Symbolic Perspective on Explainable AI. CD-MAKE (2020)
Andrea Campagner, Federico Cabitza, Davide Ciucci
Three-Way Decision for Handling Uncertainty in Machine Learning: A Narrative Review. IJCRS (2020)
Andrea Campagner, Federico Cabitza, Davide Ciucci
Three-Way Classification: Ambiguity and Abstention in Machine Learning. IJCRS (2019)
Andrea Campagner, Davide Ciucci
Orthopartitions and soft clustering: Soft mutual information measures for clustering validation. Knowl. Based Syst. 180 (2019)
Federico Cabitza, Andrea Campagner, Davide Ciucci
New Frontiers in Explainable AI: Understanding the GI to Interpret the GO. CD-MAKE (2019)
Federico Cabitza, Andrea Campagner
Who wants accurate models? Arguing for a different metrics to take classification models seriously. CoRR (2019)
Federico Cabitza, Andrea Campagner, Davide Ciucci, Andrea Seveso
Programmed Inefficiencies in DSS-Supported Human Decision Making. MDAI (2019)
Andrea Campagner, Federico Cabitza, Davide Ciucci
Exploring Medical Data Classification with Three-Way Decision Trees. HEALTHINF (2019)
Andrea Campagner, Davide Ciucci
Three-Way and Semi-supervised Decision Tree Learning Based on Orthopartitions. IPMU (2) (2018)
Andrea Campagner, Davide Ciucci
Measuring Uncertainty in Orthopairs. ECSQARU (2017)