数据挖掘方法在冠心病整合医学研究中的应用：进展与展望。
Applications of data mining methods in the integrative medical studies of coronary heart disease: progress and prospect.
机构信息
Department of General Practice, Anzhen Hospital, Capital Medical University, Beijing 100029, China.
Department of Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China.
出版信息
Evid Based Complement Alternat Med. 2014;2014:791841. doi: 10.1155/2014/791841. Epub 2014 Dec 3.
A large amount of studies show that real-world study has strong external validity than the traditional randomized controlled trials and can evaluate the effect of interventions in a real clinical setting, which open up a new path for researches of integrative medicine in coronary heart disease. However, clinical data of integrative medicine in coronary heart disease are large in amount and complex in data types, making exploring the appropriate methodology a hot topic. Data mining techniques are to analyze and dig out useful information and knowledge from the mass data to guide people's practices. The present review provides insights for the main features of data mining and their applications of integrative medical studies in coronary heart disease, aiming to analyze the progress and prospect in this field.
大量研究表明，真实世界研究比传统的随机对照试验具有更强的外部有效性，能够在真实的临床环境中评估干预措施的效果，为冠心病的整合医学研究开辟了新的途径。然而，冠心病整合医学的临床数据数量庞大，数据类型复杂，探索合适的方法成为热点问题。数据挖掘技术是从海量数据中分析和挖掘有用的信息和知识，以指导人们的实践。本综述为数据挖掘的主要特征及其在冠心病整合医学研究中的应用提供了深入了解，旨在分析该领域的进展和前景。
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