CABITZA, FEDERICO ANTONIO NICCOLO' AMEDEO

CABITZA, FEDERICO ANTONIO NICCOLO' AMEDEO  

DIPARTIMENTO DI INFORMATICA, SISTEMISTICA E COMUNICAZIONE  

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Titolo Tipologia Data di pubblicazione Autori File
Quod erat demonstrandum? - Towards a typology of the concept of explanation for the design of explainable AI 01 - Articolo su rivista 2023 Cabitza F.Campagner A. +
Aggregation models in ensemble learning: A large-scale comparison 01 - Articolo su rivista 2023 Campagner A.Ciucci D.Cabitza F.
A Confidence Interval-Based Method for Classifier Re-Calibration 02 - Intervento a convegno 2022 Campagner A.Famiglini L.Cabitza F.
Application of Machine Learning to Improve Appropriateness of Treatment in an Orthopaedic Setting of Personalized Medicine 01 - Articolo su rivista 2022 Milella, FridaFamiglini, LorenzoBanfi, GiuseppeCabitza, Federico
Color Shadows (Part I): Exploratory Usability Evaluation of Activation Maps in Radiological Machine Learning 02 - Intervento a convegno 2022 Cabitza F.Campagner A.Famiglini L. +
A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients 01 - Articolo su rivista 2022 Famiglini, LCampagner, ACabitza, F +
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 01 - Articolo su rivista 2022 Campagner A.Banfi G.Cabitza F. +
Detecting the Effect Size of Weather Conditions on Patient-Reported Outcome Measures (PROMs) 01 - Articolo su rivista 2022 Milella, FridaSeveso, AndreaFamiglini, LorenzoBanfi, GiuseppeCabitza, Federico
Global Interpretable Calibration Index, a New Metric to Estimate Machine Learning Models’ Calibration 02 - Intervento a convegno 2022 Cabitza F.Campagner A.Famiglini L.
The unbearable (technical) unreliability of automated facial emotion recognition 01 - Articolo su rivista 2022 Cabitza, FCampagner, A +
Decisions are not all equal—Introducing a utility metric based on case-wise raters’ perceptions 01 - Articolo su rivista 2022 Campagner A.Cabitza F. +
Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition 01 - Articolo su rivista 2022 Campagner A.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 01 - Articolo su rivista 2022 Milella, FridaFamiglini, LorenzoCabitza, Federico +
Re-calibrating Machine Learning Models Using Confidence Interval Bounds 02 - Intervento a convegno 2022 Campagner A.Famiglini L.Cabitza F.
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] 01 - Articolo su rivista 2021 Campagner A.Sulejmani A.Leoni V.Cabitza F. +
Assessing the impact of medical AI: A survey of physicians' perceptions 02 - Intervento a convegno 2021 Cabitza F.Campagner A. +
Machine Learning based on laboratory medicine test results in diagnosis and prognosis for COVID-19 patients: A systematic review 01 - Articolo su rivista 2021 Campagner A.Cabitza F. +
To Err is (only) Human. Reflections on How to Move from Accuracy to Trust for Medical AI 02 - Intervento a convegno 2021 Cabitza, FCampagner, ADatteri, E
Weighted Utility: A Utility Metric Based on the Case-Wise Raters’ Perceptions 02 - Intervento a convegno 2021 Campagner A.Cabitza F. +
Prediction of ICU admission for COVID-19 patients: A machine learning approach based on complete blood count data 02 - Intervento a convegno 2021 Famiglini L.Campagner A.Cabitza F. +