A Syntactic Proof of Arrow's Theorem in a Modal Logic of Social Choice Functions. - Giovanni Ciná; Ulle Endriss (AAMAS, 2015)

Proving classical theorems of social choice theory in modal logic. - Giovanni Ciná; Ulle Endriss (Auton. Agents Multi Agent Syst., 2016)

A Characterization Theorem for Trackable Updates. - Giovanni Ciná (LORI, 2017)

Bisimulation for Conditional Modalities. - Alexandru Baltag; Giovanni Ciná (Stud Logica, 2018)

Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications. - David Ruhe; Giovanni Ciná; Michele Tonutti; Daan P. de Bruin; Paul W. G. Elbers (CoRR, 2019)

Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data. - Dennis Ulmer; Lotta Meijerink; Giovanni Cinà (ML4H@NeurIPS, 2020)

Uncertainty estimation for classification and risk prediction in medical settings. - Lotta Meijerink; Giovanni Ciná; Michele Tonutti (CoRR, 2020)

Know Your Limits: Monotonicity & Softmax Make Neural Classifiers Overconfident on OOD Data. - Dennis Ulmer; Giovanni Cinà (CoRR, 2020)

Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection. - Dennis Ulmer; Giovanni Cinà (UAI, 2021)

A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients. - Adam Izdebski; Patrick J. Thoral; Robbert C. A. Lalisang; Dean M. McHugh; Robert Entjes; Nardo J. M. van der Meer; Dave A. Dongelmans; Age D. Boelens; Sander Rigter; Stefaan H. A. Hendriks; Remko de Jong; Marlijn J. A. Kamps; et al. (CoRR, 2021)

Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation. - Karina Zadorozhny; Patrick Thoral; Paul W. G. Elbers; Giovanni Cinà (CoRR, 2021)

Predicting readmission or death after discharge from the ICU: External validation and retraining of a machine learning model. - Anne De Hond; Ilse M. J. Kant; Mattia Fornasa; Giovanni Cinà; Paul W. G. Elbers; Patrick Thoral; M. Sesmu Arbous; Ewout W. Steyerberg (AMIA, 2022)

Why we do need Explainable AI for Healthcare. - Giovanni Cinà; Tabea Röber; Rob Goedhart; S. Ilker Birbil (CoRR, 2022)

Semantic match: Debugging feature attribution methods in XAI for healthcare. - Giovanni Cinà; Tabea E. Röber; Rob Goedhart; S. Ilker Birbil (CHIL, 2023)

Fixing confirmation bias in feature attribution methods via semantic match. - Giovanni Cinà; Daniel Fernandez-Llaneza; Nishant Mishra; Tabea E. Röber; Sandro Pezzelle; Iacer Calixto; Rob Goedhart; S. Ilker Birbil (CoRR, 2023)

Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury. - Izak A. R. Yasrebi-de Kom; Joanna E. Klopotowska; Dave Dongelmans; Nicolette de Keizer; Kitty J. Jager; Ameen Abu-Hanna; Giovanni Cinà (CoRR, 2023)

Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations. - Mohammad Azizmalayeri; Ameen Abu-Hanna; Giovanni Cinà (UAI, 2024)

Inducing Causal Structure Applied to Glucose Prediction for T1DM Patients. - Ana Esponera; Giovanni Cinà (CLeaR, 2025)

Unmasking the chameleons: A benchmark for out-of-distribution detection in medical tabular data. - Mohammad Azizmalayeri; Ameen Abu-Hanna; Giovanni Cinà (Int. J. Medical Informatics, 2025)

When accurate prediction models yield harmful self-fulfilling prophecies. - Wouter A. C. van Amsterdam; Nan van Geloven; Jesse H. Krijthe; Rajesh Ranganath; Giovanni Cinà (Patterns, 2025)

Inducing Causal Structure for Interpretable Neural Networks Applied to Glucose Prediction for T1DM Patients. - Ana Esponera; Giovanni Cinà (CoRR, 2025)