探讨一种机器学习方法在临床药学领域的应用进展

Research progress in application of a machine learning method in clinical pharmacy

目前基于XGBoost算法构建的模型已经广泛地运用于医学、药学领域中,而在临床药学细分领域也已实现多个方面的应用,如临床合理用药、药物不良反应预警以及药物的疗效评价及耐药性机制研究等。本文就上述应用层面进行综述,有助于临床药师深入了解XGBoost算法在临床的应用特点,增进临床用药的安全性、有效性、精准性、经济性。

At present, the model built based on XGBoost algorithm has been widely used in the fields of medicine and pharmacy, and has been applied in multiple aspects in the branch field of clinical pharmacy, such as clinical rational drug use, early warning of adverse drug reactions and efficacy evaluation and resistance mechanism of drugs.This paper reviews the applications mentioned above, which will help clinical pharmacists to deeply understand the clinical application characteristics of XGBoost algorithm, and improves the safety, effectiveness, precision and economy of clinical medication.