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.

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.