Zobrazeno 1 - 10 of 91 pro vyhledávání: '"Pwg Elbers"'
1
Outcomes of Persons With COVID-19 in Hospitals With and Without Standard Treatment With (Hydroxy)chloroquine
Autor: Marije K. Bomers, Renée A. Douma, Abraham Goorhuis, L. R. De Haan, Jacqueline Buijs, Rlm Mostard, Martijn Beudel, Mjr Quanjel, Ghh Knarren, Didier Collard, R. Renckens, Pwg Elbers, Ejg Peters, W. De Ruijter, Jonne J. Sikkens, S. Van Assen, Jpw Van Den Bergh, Auke C Reidinga, N. C. Gritters van den Oever, I. N. Vlasveld, Hazra S. Moeniralam
Publikováno v: Clinical Microbiology and Infection
ObjectiveTo compare survival of subjects with COVID-19 treated in hospitals that either did or did not routinely treat patients with hydroxychloroquine or chloroquine.MethodsWe analysed data of COVID-19 patients treated in 9 hospitals in the Netherla
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e13b357eb0dbad51123ed215f3248003
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2
[Chronic thromboembolic pulmonary hypertension: recognition, diagnosis and treatment]
Autor: Ruigrok D, Petr Symersky, Pwg, Elbers, Kamminga S, Lj, Meijboom, Hj, Bogaard
Publikováno v: Europe PubMed Central
Chronic thromboembolic pulmonary hypertension (CTEPH), characterised by pulmonary hypertension and persistent perfusion defects despite adequate anticoagulation, causes significant morbidity and mortality.- Persistent dyspnoea after acute pulmonary e
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::66d561ef54d4210267f4a1253b4aab81
https://pubmed.ncbi.nlm.nih.gov/29027516
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3
[Should every doctor be allowed to use ultrasound? Dilemmas surrounding broad application of ultrasound in clinical practice]
Autor: Pwg, Elbers, otto kamp, Jp, Sluijs, Lely R, Pr, Tuinman
Publikováno v: Europe PubMed Central
Ultrasound is rapidly gaining ground in clinical medicine. This offers distinct advantages for diagnosis and treatment. This is notably the case when moving images are created by the treating physician, who can integrate them immediately with all oth
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::baea23bd038def5fc3d79a35096d3266
https://pubmed.ncbi.nlm.nih.gov/28488552
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5
Akademický článek
Pooled Population Pharmacokinetic Analysis and Dose Recommendations for Ciprofloxacin in Intensive Care Unit Patients with Obesity.
Autor: van Rhee KP; Department of Clinical Pharmacy, Tergooi MC, Hilversum, The Netherlands.; Department of Clinical Pharmacy, St Jansdal Hospital, Harderwijk, The Netherlands.; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands., Brüggemann RJM; Department of Pharmacy and Radboud Institute of Health Science, Radboud University Medical Center, Nijmegen, The Netherlands.; Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands., Roberts JA; University of Queensland, Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.; Herston Infectious Diseases Institute (HeIDI), Metro North Health, Brisbane, Australia.; Departments of Pharmacy and Intensive Care Medicine, Royal Brisbane and Women's Hospital, Brisbane, Australia.; Division of Anaesthesiology Critical Care Emergency and Pain Medicine, Nîmes University Hospital, University of Montpellier, Nîmes, France., Sjövall F; Department of Intensive Care and Perioperative Medicine, Skane University Hospital, Malmö, Sweden.; Mitochondrial Medicine, Lund University, Lund, Sweden., van Hest RM; Department of Pharmacy and Clinical Pharmacology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands., Elbers PWG; Department of Intensive Care Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands., Abdulla A; Department of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, The Netherlands., van der Linden PD; Department of Clinical Pharmacy, Tergooi MC, Hilversum, The Netherlands., Knibbe CAJ; Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands.; Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands.
Publikováno v: Journal of clinical pharmacology [J Clin Pharmacol] 2024 Sep; Vol. 64 (9), pp. 1165-1172. Date of Electronic Publication: 2024 May 12.
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6
Akademický článek
Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data.
Autor: Jagesar AR; 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 (AII), 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. Electronic address: a.jagesar@amsterdamumc.nl., Otten M; 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 (AII), 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., Dam TA; 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 (AII), 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., Biesheuvel LA; 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 (AII), 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., Dongelmans DA; Department of Intensive Care Medicine, Amsterdam UMC, Universiteit van Amsterdam, Amsterdam, the Netherlands., Brinkman S; Department of Medical Informatics, Amsterdam UMC, Amsterdam Public Health Research Institute and National Intensive Care Evaluation (NICE) Foundation, Amsterdam, the Netherlands., Thoral PJ; 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 (AII), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands., François-Lavet V; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, 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 (AII), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands., de Keizer NF; Department of Medical Informatics, Amsterdam UMC, Amsterdam Public Health Research Institute and National Intensive Care Evaluation (NICE) Foundation, Amsterdam, the Netherlands., de Grooth HJS; Intensive Care Center, UMC Utrecht, Utrecht, 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 (AII), Amsterdam Public Health (APH), Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands.
Publikováno v: International journal of medical informatics [Int J Med Inform] 2024 Aug; Vol. 188, pp. 105477. Date of Electronic Publication: 2024 May 08.
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7
Akademický článek
Application of the Sepsis-3 criteria to describe sepsis epidemiology in the Amsterdam UMCdb intensive care dataset.
Autor: Williams CYK; Department of Medicine, Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.; Bakar Computational Health Sciences Institute, University of California, San Francisco, California, United States of America., Edinburgh T; Department of Medicine, Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.; Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom., Elbers PWG; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Thoral PJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Ercole A; Department of Medicine, Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom.; Cambridge Centre for Artificial Intelligence in Medicine, University of Cambridge, Cambridge, United Kingdom.
Publikováno v: PloS one [PLoS One] 2024 Jun 21; Vol. 19 (6), pp. e0304133. Date of Electronic Publication: 2024 Jun 21 (Print Publication: 2024).
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8
Akademický článek
Artificial intelligence to advance acute and intensive care medicine.
Autor: Biesheuvel LA; 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 (AII), Amsterdam Public Health (APH), Amsterdam UMC.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit., Dongelmans DA; Department of Intensive Care Medicine, Amsterdam Public Health (APH), Amsterdam UMC, University of Amsterdam.; National Intensive Care Evaluation Foundation, 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 (AII), Amsterdam Public Health (APH), Amsterdam UMC.
Publikováno v: Current opinion in critical care [Curr Opin Crit Care] 2024 Jun 01; Vol. 30 (3), pp. 246-250. Date of Electronic Publication: 2024 Mar 22.
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9
Akademický článek
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.
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10
Akademický článek
Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment.
Autor: Otten M; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Jagesar AR; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Dam TA; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Biesheuvel LA; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., den Hengst F; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands., Ziesemer KA; University Library, Vrije Universiteit, Amsterdam, The Netherlands., Thoral PJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., de Grooth HJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., Girbes ARJ; Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands., François-Lavet V; Quantitative Data Analytics Group, Department of Computer Science, Faculty of Science, 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, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
Publikováno v: Critical care medicine [Crit Care Med] 2024 Feb 01; Vol. 52 (2), pp. e79-e88. Date of Electronic Publication: 2023 Nov 08.
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