Thoral, Patrick

Autoantibodies against type I IFNs in patients with life-threatening COVID-19

Bastard, P., Rosen, L. B., Zhang, Q., Michailidis, E., Hoffmann, H.-H., Zhang, Y., Dorgham, K., Philippot, Q., Rosain, J., Béziat, V., et al. (2020) · Science

interferon and immune responsesSARS-CoV-2 and COVID-19 Research

Cited by 2,662

Inborn errors of type I IFN immunity in patients with life-threatening COVID-19

Zhang, Q., Bastard, P., Liu, Z., Le Pen, J., Moncada-Velez, M., Chen, J., Ogishi, M., Sabli, I. K. D., Hodeib, S., Korol, C., et al. (2020) · Science

interferon and immune responsesSARS-CoV-2 and COVID-19 Research

Cited by 2,229

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

Fleuren, L. M., Klausch, T. L. T., Zwager, C. L., Schoonmade, L. J., Guo, T., Roggeveen, L. F., Swart, E. L., Girbes, A. R. J., Thoral, P., Ercole, A., et al. (2020) · Intensive Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 755

Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity

Larsen, M. D., de Graaf, E. L., Sonneveld, M. E., Plomp, H. R., Nouta, J., Hoepel, W., Chen, H.-J., Linty, F., Visser, R., Brinkhaus, M., et al. (2021) · Science

Monoclonal and Polyclonal Antibodies ResearchGlycosylation and Glycoproteins Research

Cited by 408

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example*

Thoral, P. J., Peppink, J. M., Driessen, R. H., Sijbrands, E. J. G., Kompanje, E. J. O., Kaplan, L., Bailey, H., Kesecioglu, J., Cecconi, M., Churpek, M., et al. (2021) · Critical Care Medicine

Privacy-Preserving Technologies in DataElectronic Health Records Systems

Cited by 257

Systematic Review and Comparison of Publicly Available ICU Data Sets—A Decision Guide for Clinicians and Data Scientists

Sauer, C. M., Dam, T. A., Celi, L. A., Faltys, M., de la Hoz, M. A. A., Adhikari, L., Ziesemer, K. A., Girbes, A., Thoral, P. J., & Elbers, P. (2022) · Critical Care Medicine

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 104

Machine learning in intensive care medicine: ready for take-off?

Collaborators, R. D. R. N., Fleuren, L. M., Thoral, P., Shillan, D., Ercole, A., & Elbers, P. W. G. (2020) · Intensive Care Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 88

Transatlantic transferability of a new reinforcement learning model for optimizing haemodynamic treatment for critically ill patients with sepsis

Roggeveen, L., el Hassouni, A., Ahrendt, J., Guo, T., Fleuren, L., Thoral, P., Girbes, A. R., Hoogendoorn, M., & Elbers, P. W. (2021) · Artificial Intelligence in Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 41

Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study

van der Meijden, S. L., de Hond, A. A. H., Thoral, P. J., Steyerberg, E. W., Kant, I. M. J., Cinà, G., & Arbous, M. S. (2023) · JMIR Human Factors

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 39

Large language models in critical care

Biesheuvel, L. A., Workum, J. D., Reuland, M., van Genderen, M. E., Thoral, P., Dongelmans, D., & Elbers, P. (2025) · Journal of Intensive Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 36

Explainable Machine Learning on AmsterdamUMCdb for ICU Discharge Decision Support: Uniting Intensivists and Data Scientists

Thoral, P. J., Fornasa, M., de Bruin, D. P., Tonutti, M., Hovenkamp, H., Driessen, R. H., Girbes, A. R. J., Hoogendoorn, M., & Elbers, P. W. G. (2021) · Critical Care Explorations

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 34

Clinically Interpretable Machine Learning Models for Early Prediction of Mortality in Older Patients with Multiple Organ Dysfunction Syndrome: An International Multicenter Retrospective Study

Liu, X., DuMontier, C., Hu, P., Liu, C., Yeung, W., Mao, Z., Ho, V., Thoral, P. J., Kuo, P.-C., Hu, J., et al. (2023) · The Journals of Gerontology: Series A

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 14

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

van de Water, R., Schmidt, H., Elbers, P., Thoral, P., Arnrich, B., & Rockenschaub, P. (2023) · arXiv

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 9