Sfoglia per Autore
Belief functions and rough sets: Survey and new insights
2022 Campagner, A; Ciucci, D; Denoeux, T
The unbearable (technical) unreliability of automated facial emotion recognition
2022 Cabitza, F; Campagner, A; Mattioli, M
The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies
2021 Cabitza, F; Campagner, A
The importance of being external. methodological insights for the external validation of machine learning models in medicine
2021 Cabitza, F; Campagner, A; Soares, F; Garcia de Guadiana-Romualdo, L; Challa, F; Sulejmani, A; Seghezzi, M; Carobene, A
Ground truthing from multi-rater labeling with three-way decision and possibility theory
2021 Campagner, A; Ciucci, D; Svensson, C; Figge, M; Cabitza, F
Rough set-based feature selection for weakly labeled data
2021 Campagner, A; Ciucci, D; Hullermeier, E
To Err is (only) Human. Reflections on How to Move from Accuracy to Trust for Medical AI
2021 Cabitza, F; Campagner, A; Datteri, E
Interpretable heartbeat classification using local model-agnostic explanations on ECGs
2021 Neves, I; Folgado, D; Santos, S; Barandas, M; Campagner, A; Ronzio, L; Cabitza, F; Gamboa, H
Assessing the impact of medical AI: A survey of physicians' perceptions
2021 Cabitza, F; Campagner, A; Cavosi, V
Identification of SARS-CoV-2 positivity using machine learning methods on blood count data: External validation of state-of-the-art models. [Identificazione di positività al SARS-CoV-2 attraverso metodi di Machine Learning sui dati dell'esame emocromocitometrico: Validazione esterna di modelli allo stato dell'arte]
2021 Carobene, A; Campagner, A; Sulejmani, A; Leoni, V; Seghezzi, M; Buoro, S; Cabitza, F
Machine Learning based on laboratory medicine test results in diagnosis and prognosis for COVID-19 patients: A systematic review
2021 Carobene, A; Sabetta, E; Monteverde, E; Locatelli, M; Banfi, G; Di Resta, C; Guerranti, R; Vidali, M; Campagner, A; Cabitza, F
External validation of Machine Learning models for COVID-19 detection based on Complete Blood Count
2021 Campagner, A; Carobene, A; Cabitza, F
Weighted Utility: A Utility Metric Based on the Case-Wise Raters’ Perceptions
2021 Campagner, A; Conte, E; Cabitza, F
Learnability in “Learning from Fuzzy Labels”
2021 Campagner, A
Feature Selection and Disambiguation in Learning from Fuzzy Labels Using Rough Sets
2021 Campagner, A; Ciucci, D
The need to move away from agential-AI: Empirical investigations, useful concepts and open issues
2021 Cabitza, F; Campagner, A; Simone, C
Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests
2021 Cabitza, F; Campagner, A; Ferrari, D; Di Resta, C; Ceriotti, D; Sabetta, E; Colombini, A; De Vecchi, E; Banfi, G; Locatelli, M; Carobene, A
Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double reading
2021 Cabitza, F; Campagner, A; Sconfienza, L
Prediction of ICU admission for COVID-19 patients: A machine learning approach based on complete blood count data
2021 Famiglini, L; Bini, G; Carobene, A; Campagner, A; Cabitza, F
Unity is intelligence: a collective intelligence experiment on ecg reading to improve diagnostic performance in cardiology
2021 Ronzio, L; Campagner, A; Cabitza, F; Gensini, G
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