Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit.

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作者： Nadir,Yalçın ^[1] ; Merve,Kaşıkcı ^[2] ; Hasan Tolga,Çelik ^[3] ; Karel,Allegaert ^[4] ; Kutay,Demirkan ^[5] ; Şule,Yiğit ^[6] ; Murat,Yurdakök ^[1]

作者单位： Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, Ankara, Türkiye. ^[1] Department of Biostatistics, Faculty of Medicine, Hacettepe University, Ankara, Türkiye. ^[2] Division of Neonatology, Department of Child Health and Diseases, Faculty of Medicine, Hacettepe University, Ankara, Türkiye. ^[3] Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Belgium. ^[4] Department of Development and Regeneration, KU Leuven, Belgium. ^[5] Department of Hospital Pharmacy, Erasmus Medical Center, Rotterdam, Netherlands. ^[6]

关键词 adverse drug reaction clinical pharmacy data collection drug safety machine learning medication error newborn

DOI 10.3389/fphar.2023.1151560

PMID 37124199

发布时间 2023-05-02

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Frontiers in pharmacology

2023年14卷

1151560页

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Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit.

Frontiers in pharmacology

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Frontiers in pharmacology

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Development and validation of a machine learning-based detection system to improve precision screening for medication errors in the neonatal intensive care unit.

Frontiers in pharmacology

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Frontiers in pharmacology

相关期刊

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