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Construction and Interpretation of Prediction Model of Teicoplanin Trough Concentration via Machine Learning

OBJECTIVE: To establish an optimal model to predict the teicoplanin trough concentrations by machine learning, and explain the feature importance in the prediction model using the SHapley Additive exPlanation (SHAP) method. METHODS: A retrospective study was performed on 279 therapeutic drug monitor...

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Detalles Bibliográficos
Autores principales:	Ma, Pan, Liu, Ruixiang, Gu, Wenrui, Dai, Qing, Gan, Yu, Cen, Jing, Shang, Shenglan, Liu, Fang, Chen, Yongchuan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Medicine
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963816/ https://www.ncbi.nlm.nih.gov/pubmed/35360734 http://dx.doi.org/10.3389/fmed.2022.808969

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