An Artificial Intelligence Approach to Support Detection of Neonatal Adverse Drug Reactions Based on Severity and Probability Scores: A New Risk Score as Web-Tool.

Yalçin, Nadir; Kasikci, Merve; Çelik, Hasan Tolga; Allegaert, Karel; Demirkan, Kutay; Yigit, Sule; Yurdakök, Murat

Yalçin, Nadir; Kasikci, Merve; Çelik, Hasan Tolga; Allegaert, Karel; Demirkan, Kutay; Yigit, Sule; Yurdakök, Murat.

Afiliación

Yalçin N; Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, Ankara 06230, Turkey.
Kasikci M; Department of Biostatistics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey.
Çelik HT; Division of Neonatology, Department of Child Health and Diseases, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey.
Allegaert K; Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium.
Demirkan K; Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium.
Yigit S; Department of Hospital Pharmacy, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands.
Yurdakök M; Department of Clinical Pharmacy, Faculty of Pharmacy, Hacettepe University, Ankara 06230, Turkey.

Children (Basel) ; 9(12)2022 Nov 26.

Article en En | MEDLINE | ID: mdl-36553270

Palabras clave

adverse drug reaction; adverse event; machine learning; newborn; prediction; risk analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Children (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Turquía

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