Giovanni Cinà

21 papers A 2Misc 1Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	2-Step Agent: A Framework for the Interaction of a Decision Maker with AI Decision Support. CoRR Otto Nyberg, Fausto Carcassi, Giovanni Cinà
2026	J	`jnl`	A Causal Framework for Evaluating ICU Discharge Strategies. CoRR Sagar Nagaraj Simha, Juliette Ortholand, Dave Dongelmans, Jessica D. Workum, Olivier W. M. Thijssens, Ameen Abu-Hanna, Giovanni Cinà
2026	J	`jnl`	Improving TabPFN's Synthetic Data Generation by Integrating Causal Structure. CoRR Davide Tugnoli, Andrea De Lorenzo, Marco Virgolin, Giovanni Cinà
2026	J	`jnl`	Is my model perplexed for the right reason? Contrasting LLMs' Benchmark Behavior with Token-Level Perplexity. CoRR Zoë Prins, Samuele Punzo, Frank Wildenburg, Giovanni Cinà, Sandro Pezzelle
2025	—	`conf`	Inducing Causal Structure Applied to Glucose Prediction for T1DM Patients. CLeaR Ana Esponera, Giovanni Cinà
2025	J	`jnl`	Inducing Causal Structure for Interpretable Neural Networks Applied to Glucose Prediction for T1DM Patients. CoRR Ana Esponera, Giovanni Cinà
2025	J	`jnl`	Unmasking the chameleons: A benchmark for out-of-distribution detection in medical tabular data. Int. J. Medical Informatics Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà
2025	J	`jnl`	When accurate prediction models yield harmful self-fulfilling prophecies. Patterns Wouter A. C. van Amsterdam, Nan van Geloven, Jesse H. Krijthe, Rajesh Ranganath, Giovanni Cinà
2024	A	`conf`	Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations. UAI Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà
2024	J	`jnl`	Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations. CoRR Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà
2023	J	`jnl`	Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury. CoRR Izak A. R. Yasrebi-de Kom, Joanna E. Klopotowska, Dave Dongelmans, Nicolette de Keizer, Kitty J. Jager, Ameen Abu-Hanna, Giovanni Cinà
2023	J	`jnl`	Fixing confirmation bias in feature attribution methods via semantic match. CoRR Giovanni Cinà, Daniel Fernandez-Llaneza, Nishant Mishra, Tabea E. Röber, Sandro Pezzelle, Iacer Calixto, Rob Goedhart, S. Ilker Birbil
2023	—	`conf`	Semantic match: Debugging feature attribution methods in XAI for healthcare. CHIL Giovanni Cinà, Tabea E. Röber, Rob Goedhart, S. Ilker Birbil
2023	J	`jnl`	Semantic match: Debugging feature attribution methods in XAI for healthcare. CoRR Giovanni Cinà, Tabea E. Röber, Rob Goedhart, S. Ilker Birbil
2022	Misc	`conf`	Predicting readmission or death after discharge from the ICU: External validation and retraining of a machine learning model. AMIA Anne De Hond, Ilse M. J. Kant, Mattia Fornasa, Giovanni Cinà, Paul W. G. Elbers, Patrick Thoral, M. Sesmu Arbous, Ewout W. Steyerberg
2022	J	`jnl`	Why we do need Explainable AI for Healthcare. CoRR Giovanni Cinà, Tabea Röber, Rob Goedhart, S. Ilker Birbil
2021	J	`jnl`	A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients. CoRR 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, Marco A. A. Peters, A. Karakus, Diederik Gommers, Dharmanand Ramnarain, Evert-Jan Wils, Sefanja Achterberg, Ralph Nowitzky, Walter van den Tempel, Cornelis P. C. de Jager, Fleur G. C. A. Nooteboom, Evelien Oostdijk, Peter Koetsier, Alexander D. Cornet, Auke C. Reidinga, Wouter de Ruijter, Rob J. Bosman, Tim Frenzel, Louise C. Urlings-Strop, Paul de Jong, Ellen G. M. Smit, Olaf L. Cremer, Frits H. M. van Osch, Harald J. Faber, Judith Lens, Gert B. Brunnekreef, Barbara Festen-Spanjer, Tom Dormans, Bram Simons, A. A. Rijkeboer, Annemieke Dijkstra, M. Sesmu Arbous, Marcel Aries, Menno Beukema, Rutger van Raalte, Martijn van Tellingen, Niels C. Gritters van den Oever, Paul W. G. Elbers, Giovanni Cinà
2021	A	`conf`	Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection. UAI Dennis Ulmer, Giovanni Cinà
2021	J	`jnl`	Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation. CoRR Karina Zadorozhny, Patrick Thoral, Paul W. G. Elbers, Giovanni Cinà
2020	J	`jnl`	Know Your Limits: Monotonicity & Softmax Make Neural Classifiers Overconfident on OOD Data. CoRR Dennis Ulmer, Giovanni Cinà
2020	—	`conf`	Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data. ML4H@NeurIPS Dennis Ulmer, Lotta Meijerink, Giovanni Cinà