Andrea Campagner

Orcid: 0000-0002-0027-5157

According to our database1, Andrea Campagner authored at least 86 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures.
BMC Medical Informatics Decis. Mak., December, 2024

Ensemble Predictors: Possibilistic Combination of Conformal Predictors for Multivariate Time Series Classification.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2024

Three-way decision in machine learning tasks: a systematic review.
Artif. Intell. Rev., September, 2024

Evidence-based XAI: An empirical approach to design more effective and explainable decision support systems.
Comput. Biol. Medicine, March, 2024

Partially-defined equivalence relations: Relationship with orthopartitions and connection to rough sets.
Inf. Sci., February, 2024

Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram.
Inf. Fusion, January, 2024

Learning from fuzzy labels: Theoretical issues and algorithmic solutions.
Int. J. Approx. Reason., 2024

Never tell me the odds: Investigating pro-hoc explanations in medical decision making.
Artif. Intell. Medicine, 2024

Explanations Considered Harmful: The Impact of Misleading Explanations on Accuracy in Hybrid Human-AI Decision Making.
Proceedings of the Explainable Artificial Intelligence, 2024

Dissimilar Similarities: Comparing Human and Statistical Similarity Evaluation in Medical AI.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2024

Answering the Call to Go Beyond Accuracy: An Online Tool for the Multidimensional Assessment of Decision Support Systems.
Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, 2024

2023
A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering.
Int. J. Approx. Reason., November, 2023

Everything is varied: The surprising impact of instantial variation on ML reliability.
Appl. Soft Comput., October, 2023

A general framework for evaluating and comparing soft clusterings.
Inf. Sci., April, 2023

Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting.
Mach. Learn. Knowl. Extr., March, 2023

Aggregation models in ensemble learning: A large-scale comparison.
Inf. Fusion, 2023

Quod erat demonstrandum? - Towards a typology of the concept of explanation for the design of explainable AI.
Expert Syst. Appl., 2023

Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis.
Artif. Intell. Medicine, 2023

Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making.
Proceedings of the Explainable Artificial Intelligence, 2023

Aggregation Operators on Shadowed Sets Deriving from Conditional Events and Consensus Operators.
Proceedings of the Rough Sets - International Joint Conference, 2023

The Impact of Gender and Personality in Human-AI Teaming: The Case of Collaborative Question Answering.
Proceedings of the Human-Computer Interaction - INTERACT 2023 - 19th IFIP TC13 International Conference, York, UK, August 28, 2023

Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Credal Learning: Weakly Supervised Learning from Credal Sets.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Demo: Decision Support System Quality Assessment Tool.
Proceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter, 2023

AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

The Tower of Babel in Explainable Artificial Intelligence (XAI).
Proceedings of the Machine Learning and Knowledge Extraction, 2023

Controllable AI - An Alternative to Trustworthiness in Complex AI Systems?
Proceedings of the Machine Learning and Knowledge Extraction, 2023

Let Me Think! Investigating the Effect of Explanations Feeding Doubts About the AI Advice.
Proceedings of the Machine Learning and Knowledge Extraction, 2023

A Question of Trust: Old and New Metrics for the Reliable Assessment of Trustworthy AI.
Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023

Biomarkers for mixed dementia: a hard bone to bite? Preliminary analyses and promising results for a debated topic.
Proceedings of the 4th Italian Workshop on Artificial Intelligence for an Ageing Society co-located with 22nd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023), 2023

Toward a Perspectivist Turn in Ground Truthing for Predictive Computing.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
The unbearable (technical) unreliability of automated facial emotion recognition.
Big Data Soc., July, 2022

Uncertainty representation in dynamical systems using rough set theory.
Theor. Comput. Sci., 2022

Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition.
Sensors, 2022

Aggregation operators on shadowed sets.
Inf. Sci., 2022

Belief functions and rough sets: Survey and new insights.
Int. J. Approx. Reason., 2022

Painting the black box white: experimental findings from applying XAI to an ECG reading setting.
CoRR, 2022

Everything is Varied: The Surprising Impact of Individual Variation on ML Robustness in Medicine.
CoRR, 2022

Decisions are not all equal - Introducing a utility metric based on case-wise raters' perceptions.
Comput. Methods Programs Biomed., 2022

Orthopartitions in Knowledge Representation and Machine Learning.
Proceedings of the Rough Sets - International Joint Conference, 2022

Scikit-Weak: A Python Library for Weakly Supervised Machine Learning.
Proceedings of the Rough Sets - International Joint Conference, 2022

A Confidence Interval-Based Method for Classifier Re-Calibration.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Re-calibrating Machine Learning Models Using Confidence Interval Bounds.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2022

Comparative Assessment of Two Data Visualizations to Communicate Medical Test Results Online.
Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Rough-set Based Genetic Algorithms for Weakly Supervised Feature Selection.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

Three-way Learnability: A Learning Theoretic Perspective on Three-way Decision.
Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022

Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning.
Proceedings of the Machine Learning and Knowledge Extraction, 2022

Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models' Calibration.
Proceedings of the Machine Learning and Knowledge Extraction, 2022

A Distributional Approach for Soft Clustering Comparison and Evaluation.
Proceedings of the Belief Functions: Theory and Applications, 2022

2021
Ground truthing from multi-rater labeling with three-way decision and possibility theory.
Inf. Sci., 2021

Three-way decision and conformal prediction: Isomorphisms, differences and theoretical properties of cautious learning approaches.
Inf. Sci., 2021

The need to move away from agential-AI: Empirical investigations, useful concepts and open issues.
Int. J. Hum. Comput. Stud., 2021

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, 2021

Rough set-based feature selection for weakly labeled data.
Int. J. Approx. Reason., 2021

External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count.
Health Inf. Sci. Syst., 2021

Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double reading.
Health Inf. Sci. Syst., 2021

Toward a Perspectivist Turn in Ground Truthing for Predictive Computing.
CoRR, 2021

The importance of being external. methodological insights for the external validation of machine learning models in medicine.
Comput. Methods Programs Biomed., 2021

Interpretable heartbeat classification using local model-agnostic explanations on ECGs.
Comput. Biol. Medicine, 2021

Feature Selection and Disambiguation in Learning from Fuzzy Labels Using Rough Sets.
Proceedings of the Rough Sets - International Joint Conference, 2021

Assessing the impact of medical AI: a survey of physicians' perceptions.
Proceedings of the ICMHI 2021: 5th International Conference on Medical and Health Informatics, 2021

Learnability in "Learning from Fuzzy Labels".
Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

Weighted Utility: A Utility Metric Based on the Case-Wise Raters' Perceptions.
Proceedings of the Machine Learning and Knowledge Extraction, 2021

Prediction of ICU admission for COVID-19 patients: a Machine Learning approach based on Complete Blood Count data.
Proceedings of the 34th IEEE International Symposium on Computer-Based Medical Systems, 2021

2020
Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.
BMC Medical Informatics Decis. Mak., 2020

As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI.
BMC Medical Informatics Decis. Mak., 2020

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.
J. Medical Syst., 2020

Entropy-based shadowed set approximation of intuitionistic fuzzy sets.
Int. J. Intell. Syst., 2020

The three-way-in and three-way-out framework to treat and exploit ambiguity in data.
Int. J. Approx. Reason., 2020

Assessment and prediction of spine surgery invasiveness with machine learning techniques.
Comput. Biol. Medicine, 2020

A Formal Learning Theory for Three-Way Clustering.
Proceedings of the Scalable Uncertainty Management - 14th International Conference, 2020

Approximate Reaction Systems Based on Rough Set Theory.
Proceedings of the Rough Sets - International Joint Conference, 2020

Three-Way Decision for Handling Uncertainty in Machine Learning: A Narrative Review.
Proceedings of the Rough Sets - International Joint Conference, 2020

H-Accuracy, an Alternative Metric to Assess Classification Models in Medicine.
Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground Truth.
Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Ensemble Learning, Social Choice and Collective Intelligence - An Experimental Comparison of Aggregation Techniques.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2020

Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2020

Back to the Feature: A Neural-Symbolic Perspective on Explainable AI.
Proceedings of the Machine Learning and Knowledge Extraction, 2020

2019
Orthopartitions and soft clustering: Soft mutual information measures for clustering validation.
Knowl. Based Syst., 2019

Who wants accurate models? Arguing for a different metrics to take classification models seriously.
CoRR, 2019

Three-Way Classification: Ambiguity and Abstention in Machine Learning.
Proceedings of the Rough Sets - International Joint Conference, 2019

Programmed Inefficiencies in DSS-Supported Human Decision Making.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2019

New Frontiers in Explainable AI: Understanding the GI to Interpret the GO.
Proceedings of the Machine Learning and Knowledge Extraction, 2019

Exploring Medical Data Classification with Three-Way Decision Trees.
Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), 2019

2018
Three-Way and Semi-supervised Decision Tree Learning Based on Orthopartitions.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, 2018

2017
Measuring Uncertainty in Orthopairs.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2017


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