CABITZA, FEDERICO ANTONIO NICCOLO' AMEDEO
CABITZA, FEDERICO ANTONIO NICCOLO' AMEDEO
DIPARTIMENTO DI INFORMATICA, SISTEMISTICA E COMUNICAZIONE
Quod erat demonstrandum? - Towards a typology of the concept of explanation for the design of explainable AI
2023 Cabitza, F; Campagner, A; Malgieri, G; Natali, C; Schneeberger, D; Stoeger, K; Holzinger, A
Aggregation models in ensemble learning: A large-scale comparison
2023 Campagner, A; Ciucci, D; Cabitza, F
The unbearable (technical) unreliability of automated facial emotion recognition
2022 Cabitza, F; Campagner, A; Mattioli, M
The multicenter European Biological Variation Study (EuBIVAS): A new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands
2022 Carobene, A; Campagner, A; Uccheddu, C; Banfi, G; Vidali, M; Cabitza, F
A Confidence Interval-Based Method for Classifier Re-Calibration
2022 Campagner, A; Famiglini, L; Cabitza, F
A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients
2022 Famiglini, L; Campagner, A; Carobene, A; Cabitza, F
Re-calibrating Machine Learning Models Using Confidence Interval Bounds
2022 Campagner, A; Famiglini, L; Cabitza, F
Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models’ Calibration
2022 Cabitza, F; Campagner, A; Famiglini, L
Application of Machine Learning to Improve Appropriateness of Treatment in an Orthopaedic Setting of Personalized Medicine
2022 Milella, F; Famiglini, L; Banfi, G; Cabitza, F
How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory data
2022 Carobene, A; Milella, F; Famiglini, L; Cabitza, F
Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs)
2022 Milella, F; Seveso, A; Famiglini, L; Banfi, G; Cabitza, F
Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition
2022 Bento, N; Rebelo, J; Barandas, M; Carreiro, A; Campagner, A; Cabitza, F; Gamboa, H
Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning
2022 Cabitza, F; Campagner, A; Famiglini, L; Gallazzi, E; La Maida, G
Decisions are not all equal—Introducing a utility metric based on case-wise raters’ perceptions
2022 Campagner, A; Sternini, F; Cabitza, F
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
Three-way decision and conformal prediction: Isomorphisms, differences and theoretical properties of cautious learning approaches
2021 Campagner, A; Cabitza, F; Berjano, P; Ciucci, D
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
Weighted Utility: A Utility Metric Based on the Case-Wise Raters’ Perceptions
2021 Campagner, A; Conte, E; 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
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