Publications

Also listed on DBLP, ORCID and Google Scholar. An asterisk (*) marks equal contribution.

2026

  1. 2-Step Agent: A Framework for the Interaction of a Decision Maker with AI Decision Support Otto Nyberg*, Davide Tugnoli*, Fausto Carcassi*, Giovanni Cinà*. Preprint, 2026. arXiv
  2. A Causal Framework for Evaluating ICU Discharge Strategies Sagar Nagaraj Simha, Juliette Ortholand, Dave Anton Dongelmans, Jessica D. Workum, Olivier Thijssens, Ameen Abu–Hanna, Giovanni Cinà. Preprint, 2026. arXiv
  3. Improving TabPFN's Synthetic Data Generation by Integrating Causal Structure Davide Tugnoli, Andrea De Lorenzo, Marco Virgolin, Giovanni Cinà. Conference on Uncertainty in Artificial Intelligence (UAI), 2026, accepted. arXiv
  4. Is my model perplexed for the right reason? Contrasting LLMs' Benchmark Behavior with Token-Level Perplexity Zoë Prins, Samuele Punzo, Frank Wildenburg, Giovanni Cinà, Sandro Pezzelle. Preprint, 2026. arXiv
  5. Optimal stopping of ICU treatments under hypothetical interventions - A Scoping Review Sagar Nagaraj Simha, Ameen Abu Hanna, Dave Anton Dongelmans, Jessica D. Workum, Giovanni Cinà. Preprint, 2026. DOI
  6. Rethinking external validation for the target population: Capturing patient-level similarity with a generative model Mohammad Azizmalayeri, Ameen Abu–Hanna, Saskia Houterman, Marije M. Vis, Giovanni Cinà. Preprint, 2026. arXiv

2025

  1. Enhancing Quality of Care Assessments: Managing Atypical Patients in ICU Benchmarking in The Netherlands Mohammad Azizmalayeri, Sylvia Brinkman, Nicolette F. de Keizer, Fabian Termorshuizen, Dave Anton Dongelmans, Ameen Abu Hanna, Giovanni Cinà. Critical Care Medicine, 2025. DOI
  2. ICU readmission and mortality risk prediction: Generalizability of a multi-hospital model Tariq A. Dam, Daan de Bruin, Giovanni Cinà, Patrick J. Thoral, Paul Elbers, Corstiaan A. den Uil, Reinier F. Crane. Journal of Intensive Medicine, 2025. DOI
  3. Inducing Causal Structure Applied to Glucose Prediction for T1DM Patients Ana Esponera, Giovanni Cinà. Conference on Causal Learning and Reasoning (CLeaR), 2025.
  4. The Risks of Risk Assessment: Causal Blind Spots When Using Prediction Models for Treatment Decisions Nan van Geloven, Ruth H. Keogh, Wouter A. C. van Amsterdam, Giovanni Cinà, Jesse H. Krijthe, Niels B. Peek, Kim Luijken, Sara Magliacane, Paweł Morzywołek, Thijs van Ommen, Hein Putter, Matthew Sperrin, Junfeng Wang, Daniala L. Weir, Vanessa Didelez. Annals of Internal Medicine, 2025. DOI arXiv
  5. Vancomycin‐Induced Acute Kidney Injury in Intensive Care Patients: A Target Trial Emulation Study Using Multicenter Routinely Collected Data Izak Yasrebi‐de Kom, Kitty J. Jager, Vianda S Stel, Nicholas C Chesnaye, Ameen Abu–Hanna, Nicolette F. de Keizer, Dylan W. de Lange, Dave Anton Dongelmans, Joanna Ewa Klopotowska, Giovanni Cinà, the RESCUE Study Group. Pharmacoepidemiology and Drug Safety, 2025. DOI
  6. 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. DOI arXiv
  7. When, where, who, what, and why? The five Ws of workflow analysis for implementing an AI decision support tool at the intensive care Anne de Hond, Suzanne M. Vosslamber, Sanne Lange, Friso Engel, Mette Lindhout, Puck Noorlag, Ewout Willem Steyerberg, Giovanni Cinà, M. Sesmu Arbous. Human Factors in Healthcare, 2025. DOI
  8. Why we do need explainable AI for healthcare Giovanni Cinà, Tabea E. Röber, Rob Goedhart, Ş. İlker Birbil. Diagnostic and Prognostic Research, 2025. DOI arXiv

2024

  1. Development and clinical implementation of real-time decision support tools for ICU discharge Patrick J. Thoral, Anne de Hond, Christopher Martin Sauer, Daan P. de Bruin, Mattia Fornasa, M. Sesmu Arbous, Giovanni Cinà, Paul Elbers. Journal of Critical Care, 2024. DOI
  2. ICURE: Intensive care unit (ICU) risk evaluation for 30‐day mortality. Developing and evaluating a multivariable machine learning prediction model for patients admitted to the general ICU in Sweden Tobias Siöland, Araz Rawshani, Bengt Nellgård, Johan A Malmgren, Jonatan Oras, Keti Dalla, Giovanni Cinà, Lars Engerström, Fredrik Hessulf. Acta Anaesthesiologica Scandinavica, 2024. DOI
  3. Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations Mohammad Azizmalayeri, Ameen Abu–Hanna, Giovanni Cinà. Conference on Uncertainty in Artificial Intelligence (UAI), 2024. DOI arXiv
  4. Risk‐Based Decision Making: Estimands for Sequential Prediction Under Interventions Kim Luijken, Paweł Morzywołek, Wouter van Amsterdam, Giovanni Cinà, Jeroen Hoogland, Ruth H. Keogh, Jesse H. Krijthe, Sara Magliacane, Thijs van Ommen, Niels B. Peek, Hein Putter, Maarten van Smeden, Matthew Sperrin, Junfeng Wang, Daniala L. Weir, Vanessa Didelez, Nan van Geloven. Biometrical Journal, 2024. DOI arXiv
  5. Unmasking the chameleons: A benchmark for out-of-distribution detection in medical tabular data Mohammad Azizmalayeri, Ameen Abu–Hanna, Giovanni Cinà. International Journal of Medical Informatics, 2024. DOI arXiv

2023

  1. Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury Izak Yasrebi‐de Kom, Joanna Ewa Klopotowska, Dave Anton Dongelmans, Nicolette F. de Keizer, Kitty J. Jager, Ameen Abu–Hanna, Giovanni Cinà. Preprint, 2023. DOI arXiv
  2. Fixing confirmation bias in feature attribution methods via semantic match Giovanni Cinà, Daniel Fernández-Llaneza, Deponte, Ludovico, Nishant Mishra, Tabea E. Röber, Sandro Pezzelle, Iacer Calixto, Rob Goedhart, Ş. İlker Birbil. Preprint, 2023. DOI arXiv
  3. Semantic match: Debugging feature attribution methods in XAI for healthcare Giovanni Cinà, Tabea E. Röber, Rob Goedhart, Ş. İlker Birbil. Conference on Health, Inference, and Learning (CHIL), 2023. DOI arXiv

2022

  1. Impact of a Machine Learning–Based Decision Support System for Urinary Tract Infections: Prospective Observational Study in 36 Primary Care Practices Willem Ernst Herter, Janine Khuc, Giovanni Cinà, Bart J. Knottnerus, Mattijs Everard Numans, Maryse A. Wiewel, Tobias Nicolaas Bonten, Daan P. de Bruin, Thamar van Esch, Niels Henrik Chavannes, Robert A. Verheij. JMIR Medical Informatics, 2022. DOI
  2. Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study Siri Lise van der Meijden, Anne de Hond, Patrick J. Thoral, Ewout Willem Steyerberg, Ilse M.J. Kant, Giovanni Cinà, M. Sesmu Arbous. JMIR Human Factors, 2022. DOI
  3. Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation Karina Zadorozhny, Patrick J. Thoral, Paul Elbers, Giovanni Cinà. Studies in computational intelligence, 2022. DOI arXiv
  4. 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 Elbers, Patrick J. Thoral, M. Sesmu Arbous, Ewout Willem Steyerberg. Critical Care Medicine, 2022. DOI

2021

  1. 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 Thoral, Robbert C. A. Lalisang, Dean McHugh, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert‐Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco A. A. Peters, Marlijn J. A Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings‐Strop, Ellen G. M. Smit, D. Jannet Mehagnoul‐Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen‐Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, Arife Melike Bulut Karakuş, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, M. Sesmu Arbous, Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Paul Elbers, Giovanni Cinà. Preprint, 2021. DOI arXiv
  2. Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer, Giovanni Cinà. Conference on Uncertainty in Artificial Intelligence (UAI), 2021. DOI arXiv
  3. Predictors for extubation failure in COVID-19 patients using a machine learning approach Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik A M P J Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert‐Jan Wils, Tim Frenzel, Dave Anton Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph O. Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings‐Strop, Ellen G. M. Smit, D. Jannet Mehagnoul‐Schipper, Tom P.J. Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien A. N. Oostdijk, Auke C. Reidinga, Barbara Festen‐Spanjer, Gert B. Brunnekreef, Alexander Daniel Cornet, Walter van den Tempel, Age D. Boelens, Peter M. Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, M. Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Adam Kantorik, Tom de Ruijter, Willem Ernst Herter, Martijn Beudel, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul Elbers, the Dutch ICU Data Sharing Against Covid-19 Collaborators, Julia Koeter, Roger van Rietschote, Merijn Constantijn Reuland, Laura van Manen, Leon J. Montenij, Jasper van Bommel, Roy van den Berg, Ellen van Geest, Anisa Hana, Bas van den Bogaard, Peter Pickkers, Pim van der Heiden, Claudia van Gemeren, Arend Jan Meinders, Martha de Bruin, Emma Rademaker, Frits van Osch, Martijn D. de Kruif, Nicolas F. Schroten, Klaas Sierk Arnold, Jan Willem Fijen, Jacomar J. M. van Koesveld, Koen S. Simons, Joost A. M. Labout, Bart van de Gaauw, Michael A. Kuiper, Albertus Beishuizen, Dennis Geutjes, Johan Lutisan, Bart P. X. Grady, Remko van den Akker, Tom A. Rijpstra, Wim G. Boersma, Daniël Pretorius, Menno Beukema, Bram Simons, A. A. Rijkeboer, Marcel J H Ariës, Niels C. Gritters van den Oever, Martijn van Tellingen. Critical Care, 2021. DOI
  4. Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse Lucas M. Fleuren, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Tariq A. Dam, Diederik A M P J Gommers, Olaf L. Cremer, Rob J. Bosman, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Nardo J. M. van der Meer, Sander Rigter, Evert‐Jan Wils, Tim Frenzel, Dave Anton Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph O. Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings‐Strop, Ellen G. M. Smit, D. Jannet Mehagnoul‐Schipper, Tom P.J. Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Evelien A. N. Oostdijk, Auke C. Reidinga, Barbara Festen‐Spanjer, Gert B. Brunnekreef, Alexander Daniel Cornet, Walter van den Tempel, Age D. Boelens, Peter M. Koetsier, Judith Lens, Sefanja Achterberg, Harald J. Faber, Ali Karakuş, Menno Beukema, Robert Entjes, Paul de Jong, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Martijn Beudel, Nicolet F. de Keizer, Mark Hoogendoorn, Armand R. J. Girbes, Willem Ernst Herter, Paul Elbers, Patrick J. Thoral, Dutch ICU Data Sharing Against COVID-19 Collaborators, Thijs C. D. Rettig, Merijn Constantijn Reuland, Laura van Manen, Leon J. Montenij, Jasper van Bommel, Roy van den Berg, Ellen van Geest, Anisa Hana, Wim G. Boersma, Bas van den Bogaard, Peter Pickkers, Pim van der Heiden, Claudia van Gemeren, Arend Jan Meinders, Martha de Bruin, Emma Rademaker, Frits van Osch, Martijn D. de Kruif, Nicolas F. Schroten, Klaas Sierk Arnold, Jan Willem Fijen, Jacomar J. M. van Koesveld, Koen S. Simons, Joost A. M. Labout, Bart van de Gaauw, Michael A. Kuiper, Albertus Beishuizen, Dennis Geutjes, Johan Lutisan, Bart P. X. Grady, Remko van den Akker, Bram Simons, A. A. Rijkeboer, M. Sesmu Arbous, Marcel J H Ariës, Niels C. Gritters van den Oever, Martijn van Tellingen, Annemieke Dijkstra, Rutger van Raalte, Luca F. Roggeveen, Fuda van Diggelen. Intensive Care Medicine Experimental, 2021. DOI
  5. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik A M P J Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert‐Jan Wils, Tim Frenzel, Dave Anton Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph O. Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings‐Strop, Ellen G. M. Smit, D. Jannet Mehagnoul‐Schipper, Tom P.J. Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien A. N. Oostdijk, Auke C. Reidinga, Barbara Festen‐Spanjer, Gert B. Brunnekreef, Alexander Daniel Cornet, Walter van den Tempel, Age D. Boelens, Peter M. Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, M. Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn-Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Martijn Beudel, Willem Ernst Herter, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul Elbers. Critical Care, 2021. DOI
  6. The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge Juliette de Vos, Laurenske A. Visser, Aletta A. de Beer, Mattia Fornasa, Patrick J. Thoral, Paul Elbers, Giovanni Cinà. Value in Health, 2021. DOI

2020

  1. Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data Dennis Ulmer, Lotta Meijerink, Giovanni Cinà. Machine Learning for Health (ML4H) at NeurIPS (ML4H), 2020. DOI arXiv
  2. Uncertainty estimation for classification and risk prediction on medical tabular data Lotta Meijerink, Giovanni Cinà, Michele Tonutti. Preprint, 2020. DOI arXiv

2019

  1. Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications David Ruhe, Giovanni Cinà, Michele Tonutti, de Bruin, Daan, Paul Elbers. Preprint, 2019. DOI arXiv

2017

  1. A Characterization Theorem for Trackable Updates Giovanni Cinà. Lecture notes in computer science, 2017. DOI
  2. Bisimulation for Conditional Modalities Alexandru Baltag, Giovanni Cinà. Studia Logica, 2017. DOI
  3. Categories for the working modal logician Giovanni Cinà. PhD thesis, Institute for Logic, Language and Computation, University of Amsterdam, 2017.

2016

  1. Bisimulation and path logic for sheaves: contextuality and beyond Giovanni Cinà, Sebastian Enqvist. ILLC Technical Reports, 2016.
  2. MIXING CATEGORIES AND MODAL LOGICS IN THE QUANTUM SETTING Giovanni Cinà. 2016. DOI
  3. Proving classical theorems of social choice theory in modal logic Giovanni Cinà, Ulle Endriss. Autonomous Agents and Multi-Agent Systems, 2016. DOI

2015

  1. A Syntactic Proof of Arrow's Theorem in a Modal Logic of Social Choice Functions Giovanni Cinà, Ulle Endriss. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.