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大数据时代医学数据库与数据挖掘技术简介。

Brief introduction of medical database and data mining technology in big data era.

机构信息

Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.

School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.

出版信息

J Evid Based Med. 2020 Feb;13(1):57-69. doi: 10.1111/jebm.12373. Epub 2020 Feb 22.

DOI:10.1111/jebm.12373
PMID:32086994
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7065247/
Abstract

Data mining technology can search for potentially valuable knowledge from a large amount of data, mainly divided into data preparation and data mining, and expression and analysis of results. It is a mature information processing technology and applies database technology. Database technology is a software science that researches manages, and applies databases. The data in the database are processed and analyzed by studying the underlying theory and implementation methods of the structure, storage, design, management, and application of the database. We have introduced several databases and data mining techniques to help a wide range of clinical researchers better understand and apply database technology.

摘要

数据挖掘技术可以从大量数据中搜索潜在有价值的知识,主要分为数据准备和数据挖掘以及结果的表示和分析。它是一种成熟的信息处理技术,应用数据库技术。数据库技术是研究、管理和应用数据库的软件科学。通过研究数据库的结构、存储、设计、管理和应用的基础理论和实现方法,对数据库中的数据进行处理和分析。我们已经介绍了几种数据库和数据挖掘技术,以帮助广泛的临床研究人员更好地理解和应用数据库技术。

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本文引用的文献

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Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.195 个国家 1990 年至 2017 年饮食风险对健康的影响:2017 年全球疾病负担研究的系统分析。
Lancet. 2019 May 11;393(10184):1958-1972. doi: 10.1016/S0140-6736(19)30041-8. Epub 2019 Apr 4.
2
Description of Clinical Characteristics of VAP Patients in MIMIC Database.MIMIC数据库中VAP患者的临床特征描述。
Front Pharmacol. 2019 Feb 4;10:62. doi: 10.3389/fphar.2019.00062. eCollection 2019.
3
Indoor tanning and skin cancer in Canada: A meta-analysis and attributable burden estimation.加拿大室内晒黑与皮肤癌:荟萃分析与归因负担评估。
Cancer Epidemiol. 2019 Apr;59:1-7. doi: 10.1016/j.canep.2019.01.004. Epub 2019 Jan 10.
4
Prognostic nomogram for acute pancreatitis patients: An analysis of publicly electronic healthcare records in intensive care unit.急性胰腺炎患者的预后列线图:重症监护病房公共电子医疗记录分析。
J Crit Care. 2019 Apr;50:213-220. doi: 10.1016/j.jcrc.2018.10.030. Epub 2018 Nov 5.
5
Maternal mortality ratios in 2852 Chinese counties, 1996-2015, and achievement of Millennium Development Goal 5 in China: a subnational analysis of the Global Burden of Disease Study 2016.2016 年全球疾病负担研究:1996-2015 年中国 2852 个县孕产妇死亡率及中国千年发展目标 5 的实现情况:省级分析。
Lancet. 2019 Jan 19;393(10168):241-252. doi: 10.1016/S0140-6736(18)31712-4. Epub 2018 Dec 13.
6
Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.全球、区域和国家层面 195 个国家和地区 1990 年至 2017 年 354 种疾病和伤害导致的发病率、患病率和伤残损失寿命年:基于 2017 年全球疾病负担研究的系统分析。
Lancet. 2018 Nov 10;392(10159):1789-1858. doi: 10.1016/S0140-6736(18)32279-7. Epub 2018 Nov 8.
7
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Gynecol Oncol. 2018 Nov;151(2):269-274. doi: 10.1016/j.ygyno.2018.08.041. Epub 2018 Sep 22.