Academic Bibliography

Search 200 years of publications by Ghent University researchers.

Thomas De Corte

ORCID iD: 0000-0001-5011-6640

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- Journal Article
- A1
- open access
Towards trustful machine learning for antimicrobial therapy using an explainable artificial intelligence dashboard

Thomas De Corte (UGent) , Jarne Verhaeghe (UGent) , Femke Ongenae (UGent) , Jan De Waele (UGent) and Sofie Van Hoecke (UGent)

(2025) APPLIED SCIENCES-BASEL. 15(20).
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- Journal Article
- A1
- open access
The impact of intensive care strain on patients' outcomes : a multinational observational cohort (UNITE-COVID) study

Katharina Kohler, Thomas De Corte (UGent) , Massimiliano Greco, Pedro Povoa, Maurizio Cecconi, Marlies Ostermann, Jan De Waele (UGent) , Andrew Conway Morris, Jolien Van Hecke (UGent) and [missing] UNITE-COVID Investigators

(2025) CRITICAL CARE. 29(1).
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- Journal Article
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Evaluating early mobilisation in critically ill COVID-19 patients : secondary analysis from the ESICM UNITE-COVID-II multicentre observational study

Maximilian Markus, Maximilian Lindholz, Nils Daum, Anne Pohrt, Elie Azoulay, Maurizio Cecconi, Giuseppe Citerio, Thomas De Corte (UGent) , Frantisek Duska, Laura Galarza, et al.

(2025) ANAESTHESIA CRITICAL CARE & PAIN MEDICINE. 44(4).
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- Conference Paper
- C1
- open access
Designing a pharmacokinetic machine learning model for optimizing beta-lactam antimicrobial dosing in critically ill patients

Jarne Verhaeghe (UGent) , Thomas De Corte (UGent) , Jan De Waele (UGent) , Femke Ongenae (UGent) and Sofie Van Hoecke (UGent)

(2024) ICMHI '24 : Proceedings of the 2024 8th International Conference on Medical and Health Informatics. p.311-317
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- PhD Thesis
Antimicrobial stewardship in the intensive care unit : evolving challenges and data science opportunities

Thomas De Corte (UGent)

(2024)
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Characteristics of co-infection and secondary infection amongst critically ill COVID-19 patients in the first two waves of the pandemic

Thomas De Corte (UGent) , Katharina Kohler, Maurizio Cecconi, Jan De Waele (UGent) , Andrew Conway Morris, Elie Azoulay, Massimo Antonelli, Giuseppe Citerio, Andy Conway Morris, Frantisek Duska, et al.

(2024) INTENSIVE CARE MEDICINE. 50. p.989-993
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- Conference Paper
- C3
- open access
Expectations and readiness of ICU physicians to use AI in clinical practice : a multicentre survey study

Thomas De Corte (UGent) , Laura Van Maele, Jona Dietvorst, Jarne Verhaeghe (UGent) , Ann Vandendriessche, N De Neve, Sofie Vanderhaeghen (UGent) , A Dumoulin, W. Temmerman, B Dewulf, et al.

(2023) ESICM, 36th Annual congress, Abstracts.
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Towards artificial intelligence as a decision support tool to combat AMR in the ICU

Thomas De Corte (UGent) , Jarne Verhaeghe (UGent) , Femke Ongenae (UGent) , Sofie Van Hoecke (UGent) and Jan De Waele (UGent)

(2023) ICU MANAGEMENT. 23(4). p.144-147
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Early mobilisation in critically ill COVID-19 patients : a subanalysis of the ESICM-initiated UNITE-COVID observational study

Philipp Kloss, Maximilian Lindholz, Annette Milnik, Elie Azoulay, Maurizio Cecconi, Giuseppe Citerio, Thomas De Corte (UGent) , Frantisek Duska, Laura Galarza, Massimiliano Greco, et al.

(2023) ANNALS OF INTENSIVE CARE. 13(1).
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- Journal Article
- A1
- open access
Generalizable calibrated machine learning models for real-time atrial fibrillation risk prediction in ICU patients

Jarne Verhaeghe (UGent) , Thomas De Corte (UGent) , Christopher M. Sauer, Tom Hendriks, Olivier W.M. Thijssens, Femke Ongenae (UGent) , Paul Elbers, Jan De Waele (UGent) and Sofie Van Hoecke (UGent)

(2023) INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS. 175.

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