Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

被引:0
|
作者
Jarne Verhaeghe
Sofie A. M. Dhaese
Thomas De Corte
David Vander Mijnsbrugge
Heleen Aardema
Jan G. Zijlstra
Alain G. Verstraete
Veronique Stove
Pieter Colin
Femke Ongenae
Jan J. De Waele
Sofie Van Hoecke
机构
[1] Ghent University - imec,IDLab, Department of Information Technology
[2] Ghent University,Department of Internal Medicine and Pediatrics
[3] University Medical Center Groningen,Department of Critical Care
[4] Ghent University,Department of Diagnostic Sciences
[5] University Medical Center Groningen,Department of Anesthesiology
[6] Ghent University Hospital,Department of Critical Care Medicine
来源
BMC Medical Informatics and Decision Making | / 22卷
关键词
Critically ill; Intensive care; Machine learning; Piperacillin/tazobactam; Population pharmacokinetics; Therapeutic drug monitoring; Uncertainty quantification;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients
    Verhaeghe, Jarne
    Dhaese, Sofie A. M.
    De Corte, Thomas
    Vander Mijnsbrugge, David
    Aardema, Heleen
    Zijlstra, Jan G.
    Verstraete, Alain G.
    Stove, Veronique
    Colin, Pieter
    Ongenae, Femke
    De Waele, Jan J.
    Van Hoecke, Sofie
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2022, 22 (01)
  • [2] Measuring Unbound Versus Total Piperacillin Concentrations in Plasma of Critically Ill Patients: Methodological Issues and Relevance
    Colman, Sofie
    Stove, Veronique
    De Waele, Jan J.
    Verstraete, Alain G.
    THERAPEUTIC DRUG MONITORING, 2019, 41 (03) : 325 - 330
  • [3] Variability of piperacillin concentrations in relation to tazobactam concentrations in critically ill patients
    Zander, Johannes
    Doebbeler, Gundula
    Nagel, Dorothea
    Scharf, Christina
    Huseyn-Zada, Mikayil
    Jung, Jette
    Frey, Lorenz
    Vogeser, Michael
    Zoller, Michael
    INTERNATIONAL JOURNAL OF ANTIMICROBIAL AGENTS, 2016, 48 (04) : 435 - 439
  • [4] Machine learning models to predict electroencephalographic seizures in critically ill children
    Hu, Jian
    Fung, France W.
    Jacobwitz, Marin
    Parikh, Darshana S.
    Vala, Lisa
    Donnelly, Maureen
    Topjian, Alexis A.
    Abend, Nicholas S.
    Xiao, Rui
    SEIZURE-EUROPEAN JOURNAL OF EPILEPSY, 2021, 87 : 61 - 68
  • [5] Posaconazole Plasma Concentrations in Critically Ill Patients
    Ray, John
    Campbell, Lewis
    Rudham, Sam
    Quoc Nguyen
    Marriott, Deborah
    THERAPEUTIC DRUG MONITORING, 2011, 33 (04) : 387 - 392
  • [6] Using Machine Learning to Predict Hyperchloremia in Critically Ill Patients
    Yeh, Pete
    Pan, Yiheng
    Sanchez-Pinto, L. Nelson
    Luo, Yuan
    2019 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2019, : 1703 - 1707
  • [7] An Integral Pharmacokinetic Analysis of Piperacillin and Tazobactam in Plasma and Urine in Critically Ill Patients
    Wallenburg, Eveline
    ter Heine, Rob
    Schouten, Jeroen A.
    Raaijmakers, Jelmer
    ten Oever, Jaap
    Kolwijck, Eva
    Burger, David M.
    Pickkers, Peter
    Frenzel, Tim
    Bruggemann, Roger J. M.
    CLINICAL PHARMACOKINETICS, 2022, 61 (06) : 907 - 918
  • [8] Development, deployment, and continuous monitoring of a machine learning model to predict respiratory failure in critically ill patients
    Lam, Jonathan Y.
    Lu, Xiaolei
    Shashikumar, Supreeth P.
    Lee, Ye Sel
    Miller, Michael
    Pour, Hayden
    Boussina, Aaron E.
    Pearce, Alex K.
    Malhotra, Atul
    Nemati, Shamim
    JAMIA OPEN, 2024, 7 (04)
  • [9] Plasma erythromycin concentrations predict feeding outcomes in critically ill patients with feed intolerance
    Nguyen, Nam Q.
    Grgurinovich, Nick
    Bryant, Laura K.
    Burgstad, Carly M.
    Chapman, Marianne J.
    Holloway, Richard H.
    Mangoni, Arduino A.
    Fraser, Robert J. L.
    CRITICAL CARE MEDICINE, 2011, 39 (04) : 868 - 871
  • [10] Development and validation of the creatinine clearance predictor machine learning models in critically ill adults
    Chao-Yuan Huang
    Fabian Güiza
    Pieter Wouters
    Liese Mebis
    Giorgia Carra
    Jan Gunst
    Philippe Meersseman
    Michael Casaer
    Greet Van den Berghe
    Greet De Vlieger
    Geert Meyfroidt
    Critical Care, 27