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机器学习在临床药物治疗中的研究进展 被引量:7

Research Progress of Machine Learning in Clinical Drug Therapy
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摘要 随着真实世界研究、精准治疗等概念的提出和发展,科研工作者对医疗大数据处理的需求不断增大。机器学习技术因在处理海量、高维数据及开展预测研究等方面具有独特优势,故而近些年在医学领域的应用不断深入。除应用于疾病诊断、影像识别和风险预测外,越来越多的研究证明机器学习可被应用于临床药物治疗的决策支持相关研究中。本文就机器学习在临床药物治疗中的研究进展予以综述。 With the advancement and development of concepts such as real-world research and precision treatment,the demand of researchers for medical big data processing keeps increasing.Because machine learning technology has unique advantages in processing massive,high-dimensional data and conducting predictive research,it has been deeply applied in the medical field in recent years.In addition to the application in disease diagnosis,image recognition and risk prediction,more and more studies have proved that machine learning can be applied to the decision support related research of clinical drug treatment.This article reviews the research progress of machine learning in clinical drug therapy.
作者 吴行伟 刘馨宇 龙恩武 童荣生 WU Xingwei;LIU Xinyu;LONG Enwu;TONG Rongsheng(Department of Pharmacy,Sichuan Academy of Medical Sciences&Sichuan Provincial People's Hospital,Chengdu 610072,China;Personalized Drug Therapy Key Laboratory of Sichuan Province,School of Medicine,University of Electronic Science and Technology of China,Chengdu 610072,China)
出处 《中国全科医学》 CAS 北大核心 2022年第2期254-258,共5页 Chinese General Practice
基金 国家自然科学基金资助项目(72004020) 国家重点研发计划(2020YFC2005506)。
关键词 机器学习 临床药物治疗 真实世界研究 精准治疗 综述 Machine learning Clinical drug therapy Real world research Accurate treatment Review
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