论文标题
药剂师评估药物订单与机器学习模型的预测
Comparison of pharmacist evaluation of medication orders with predictions of a machine learning model
论文作者
论文摘要
这项工作的目的是评估无监督的机器学习模型的临床性能，该模型旨在识别异常的药物订单和药理特征。我们在2020年4月至2020年8月之间进行了一项前瞻性研究，其中25名临床药剂师二分法（典型或非典型）的药物订单为12,471个药物订单和1,356个药理学特征。基于AUPR，订单的性能较差，但对概况令人满意。药剂师认为该模型是有用的筛选工具。
The objective of this work was to assess the clinical performance of an unsupervised machine learning model aimed at identifying unusual medication orders and pharmacological profiles. We conducted a prospective study between April 2020 and August 2020 where 25 clinical pharmacists dichotomously (typical or atypical) rated 12,471 medication orders and 1,356 pharmacological profiles. Based on AUPR, performance was poor for orders, but satisfactory for profiles. Pharmacists considered the model a useful screening tool.
