Reinforcement learning for intensive care medicine: actionable clinical insights from novel approaches to reward shaping and off-policy model evaluation.

Autor: Roggeveen LF; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AI&II), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Hassouni AE; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., de Grooth HJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AI&II), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AI&II), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Hoogendoorn M; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence (C4I), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Institute for Infection and Immunity (AI&II), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. p.elbers@amsterdamumc.nl.

Publikováno v: Intensive care medicine experimental [Intensive Care Med Exp] 2024 Mar 25; Vol. 12 (1), pp. 32. Date of Electronic Publication: 2024 Mar 25.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

Autor: Dam TA; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. t.dam@amsterdamumc.nl., Roggeveen LF; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., van Diggelen F; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, VU University, Amsterdam, The Netherlands., Fleuren LM; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Jagesar AR; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Otten M; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., de Vries HJ; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Gommers D; Department of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands., Cremer OL; Intensive Care, UMC Utrecht, Utrecht, The Netherlands., Bosman RJ; ICU, OLVG, Amsterdam, The Netherlands., Rigter S; Department of Anesthesiology and Intensive Care, St. Antonius Hospital, Nieuwegein, The Netherlands., Wils EJ; Department of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands., Frenzel T; Department of Intensive Care Medicine, Radboud University Medical Center, Nijmegen, The Netherlands., Dongelmans DA; Department of Intensive Care Medicine, Amsterdam UMC, Amsterdam, The Netherlands., de Jong R; Intensive Care, Bovenij Ziekenhuis, Amsterdam, The Netherlands., Peters MAA; Intensive Care, Canisius Wilhelmina Ziekenhuis, Nijmegen, The Netherlands., Kamps MJA; Intensive Care, Catharina Ziekenhuis Eindhoven, Eindhoven, The Netherlands., Ramnarain D; Department of Intensive Care, ETZ Tilburg, Tilburg, The Netherlands., Nowitzky R; Intensive Care, HagaZiekenhuis, Den Haag, The Netherlands., Nooteboom FGCA; Intensive Care, Laurentius Ziekenhuis, Roermond, The Netherlands., de Ruijter W; Department of Intensive Care Medicine, Northwest Clinics, Alkmaar, The Netherlands., Urlings-Strop LC; Intensive Care, Reinier de Graaf Gasthuis, Delft, The Netherlands., Smit EGM; Intensive Care, Spaarne Gasthuis, Haarlem en Hoofddorp, The Netherlands., Mehagnoul-Schipper DJ; Intensive Care, VieCuri Medisch Centrum, Venlo, The Netherlands., Dormans T; Intensive Care, Zuyderland MC, Heerlen, The Netherlands., de Jager CPC; Department of Intensive Care, Jeroen Bosch Ziekenhuis, Den Bosch, The Netherlands., Hendriks SHA; Intensive Care, Albert Schweitzerziekenhuis, Dordrecht, The Netherlands., Achterberg S; ICU, Haaglanden Medisch Centrum, Den Haag, The Netherlands., Oostdijk E; ICU, Maasstad Ziekenhuis Rotterdam, Rotterdam, The Netherlands., Reidinga AC; ICU, SEH, BWC, Martiniziekenhuis, Groningen, The Netherlands., Festen-Spanjer B; Intensive Care, Ziekenhuis Gelderse Vallei, Ede, The Netherlands., Brunnekreef GB; Department of Intensive Care, Ziekenhuisgroep Twente, Almelo, The Netherlands., Cornet AD; Department of Intensive Care, Medisch Spectrum Twente, Enschede, The Netherlands., van den Tempel W; Department of Intensive Care, Ikazia Ziekenhuis Rotterdam, Rotterdam, The Netherlands., Boelens AD; Antonius Ziekenhuis Sneek, Sneek, The Netherlands., Koetsier P; Intensive Care, Medisch Centrum Leeuwarden, Leeuwarden, The Netherlands., Lens J; ICU, IJsselland Ziekenhuis, Capelle aan den IJssel, The Netherlands., Faber HJ; ICU, WZA, Assen, The Netherlands., Karakus A; Department of Intensive Care, Diakonessenhuis Hospital, Utrecht, The Netherlands., Entjes R; Department of Intensive Care, Adrz, Goes, The Netherlands., de Jong P; Department of Anesthesia and Intensive Care, Slingeland Ziekenhuis, Doetinchem, The Netherlands., Rettig TCD; Department of Anesthesiology, Intensive Care and Pain Medicine, Amphia Ziekenhuis, Breda, The Netherlands., Arbous S; LUMC, Leiden, The Netherlands., Vonk SJJ; Pacmed, Amsterdam, The Netherlands., Machado T; Pacmed, Amsterdam, The Netherlands., Herter WE; Pacmed, Amsterdam, The Netherlands., de Grooth HJ; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Thoral PJ; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Hoogendoorn M; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, VU University, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.

Publikováno v: Annals of intensive care [Ann Intensive Care] 2022 Oct 20; Vol. 12 (1), pp. 99. Date of Electronic Publication: 2022 Oct 20.

Why we should sample sparsely and aim for a higher target: Lessons from model-based therapeutic drug monitoring of vancomycin in intensive care patients.

Autor: Guo T; Department of Intensive Care Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Medical Data Science, Research VUmc Intensive Care, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands., van Hest RM; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands., Fleuren LM; Department of Intensive Care Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Medical Data Science, Research VUmc Intensive Care, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Roggeveen LF; Department of Intensive Care Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Medical Data Science, Research VUmc Intensive Care, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Bosman RJ; Intensive Care Unit, OLVG Oost, Amsterdam, The Netherlands., van der Voort PHJ; Intensive Care Unit, OLVG Oost, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Medical Data Science, Research VUmc Intensive Care, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Mathot RAA; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands., van Hasselt JGC; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Medical Data Science, Research VUmc Intensive Care, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Publikováno v: British journal of clinical pharmacology [Br J Clin Pharmacol] 2021 Mar; Vol. 87 (3), pp. 1234-1242. Date of Electronic Publication: 2020 Aug 17.

Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients.

Autor: Guo T; Department of Intensive Care Medicine | Research VUmc Intensive Care (REVIVE) | Amsterdam Cardiovascular Sciences (ACS) | Amsterdam Medical Data Science (AMDS), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. t.guo@amsterdamumc.nl.; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands. t.guo@amsterdamumc.nl.; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands. t.guo@amsterdamumc.nl., van Hest RM; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands., Zwep LB; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands.; Mathematical Institute, Leiden University, Leiden, The Netherlands., Roggeveen LF; Department of Intensive Care Medicine | Research VUmc Intensive Care (REVIVE) | Amsterdam Cardiovascular Sciences (ACS) | Amsterdam Medical Data Science (AMDS), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Fleuren LM; Department of Intensive Care Medicine | Research VUmc Intensive Care (REVIVE) | Amsterdam Cardiovascular Sciences (ACS) | Amsterdam Medical Data Science (AMDS), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Bosman RJ; Intensive Care Unit, OLVG Oost, Amsterdam, The Netherlands., van der Voort PHJ; Intensive Care Unit, OLVG Oost, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine | Research VUmc Intensive Care (REVIVE) | Amsterdam Cardiovascular Sciences (ACS) | Amsterdam Medical Data Science (AMDS), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Mathot RAA; Department of Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine | Research VUmc Intensive Care (REVIVE) | Amsterdam Cardiovascular Sciences (ACS) | Amsterdam Medical Data Science (AMDS), Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., van Hasselt JGC; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, The Netherlands.

Publikováno v: Pharmaceutical research [Pharm Res] 2020 Aug 23; Vol. 37 (9), pp. 171. Date of Electronic Publication: 2020 Aug 23.

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

Autor: Fleuren LM; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands. l.fleuren@amsterdamumc.nl.; Computational Intelligence Group, Department of Computer Science, VU Amsterdam, Amsterdam, The Netherlands. l.fleuren@amsterdamumc.nl., Klausch TLT; Department of Epidemiology and Biostatistics, Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Zwager CL; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Schoonmade LJ; Medical Library, Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Guo T; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Roggeveen LF; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands.; Computational Intelligence Group, Department of Computer Science, VU Amsterdam, Amsterdam, The Netherlands., Swart EL; Department of Pharmacy, Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Thoral P; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands., Ercole A; Division of Anaesthesia, University of Cambridge, Cambridge, UK.; Data Science Section, European Society of Intensive Care Medicine, Brussels, Belgium., Hoogendoorn M; Computational Intelligence Group, Department of Computer Science, VU Amsterdam, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, location VUmc, VU Amsterdam, Amsterdam, The Netherlands.; Data Science Section, European Society of Intensive Care Medicine, Brussels, Belgium.

Publikováno v: Intensive care medicine [Intensive Care Med] 2020 Mar; Vol. 46 (3), pp. 383-400. Date of Electronic Publication: 2020 Jan 21.