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

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          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.

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          Most cited references68

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          Sharing Detailed Research Data Is Associated with Increased Citation Rate

          Background Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. Principal Findings We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression. Significance This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.
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            Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database.

            We sought to develop an intensive care unit research database applying automated techniques to aggregate high-resolution diagnostic and therapeutic data from a large, diverse population of adult intensive care unit patients. This freely available database is intended to support epidemiologic research in critical care medicine and serve as a resource to evaluate new clinical decision support and monitoring algorithms. Data collection and retrospective analysis. All adult intensive care units (medical intensive care unit, surgical intensive care unit, cardiac care unit, cardiac surgery recovery unit) at a tertiary care hospital. Adult patients admitted to intensive care units between 2001 and 2007. None. The Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database consists of 25,328 intensive care unit stays. The investigators collected detailed information about intensive care unit patient stays, including laboratory data, therapeutic intervention profiles such as vasoactive medication drip rates and ventilator settings, nursing progress notes, discharge summaries, radiology reports, provider order entry data, International Classification of Diseases, 9th Revision codes, and, for a subset of patients, high-resolution vital sign trends and waveforms. Data were automatically deidentified to comply with Health Insurance Portability and Accountability Act standards and integrated with relational database software to create electronic intensive care unit records for each patient stay. The data were made freely available in February 2010 through the Internet along with a detailed user's guide and an assortment of data processing tools. The overall hospital mortality rate was 11.7%, which varied by critical care unit. The median intensive care unit length of stay was 2.2 days (interquartile range, 1.1-4.4 days). According to the primary International Classification of Diseases, 9th Revision codes, the following disease categories each comprised at least 5% of the case records: diseases of the circulatory system (39.1%); trauma (10.2%); diseases of the digestive system (9.7%); pulmonary diseases (9.0%); infectious diseases (7.0%); and neoplasms (6.8%). MIMIC-II documents a diverse and very large population of intensive care unit patient stays and contains comprehensive and detailed clinical data, including physiological waveforms and minute-by-minute trends for a subset of records. It establishes a new public-access resource for critical care research, supporting a diverse range of analytic studies spanning epidemiology, clinical decision-rule development, and electronic tool development.
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              Dynamics of the Chinese diet and the role of urbanicity, 1991-2011.

              China's food consumption patterns and eating and cooking behaviours changed dramatically between 1991 and 2011. Macronutrient composition has shifted towards fats, and protein and sodium intakes remain high and potassium intake low. The rapid decline in intake of coarse grains and, later, of refined grains and increases in intake of edible oils and animal-source foods accompanied by major eating and cooking behaviour shifts are leading to what might be characterized as an unhealthy Western type of diet, often based on traditional recipes with major additions and changes. The most popular animal-source food is pork, and consumption of poultry and eggs is increasing. The changes in cooking and eating styles include a decrease in the proportion of food steamed, baked, or boiled, and an increase in snacking and eating away from home. Prior to the last decade, there was essentially no snacking in China except for hot water or green tea. Most recently, the intake of foods high in added sugar has increased. The dietary shifts are affected greatly by the country's urbanization. The future, as exemplified by the diet of the three mega cities, promises major growth in consumption of processed foods and beverages. © 2014 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of the International Association for the Study of Obesity.
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                Author and article information

                Contributors
                tlil@jnu.edu.cn
                lyujun2019@163.com
                Journal
                J Evid Based Med
                J Evid Based Med
                10.1111/(ISSN)1756-5391
                JEBM
                Journal of Evidence-Based Medicine
                John Wiley and Sons Inc. (Hoboken )
                1756-5391
                22 February 2020
                February 2020
                : 13
                : 1 ( doiID: 10.1111/jebm.v13.1 )
                : 57-69
                Affiliations
                [ 1 ] Department of Clinical Research The First Affiliated Hospital of Jinan University Guangzhou Guangdong China
                [ 2 ] School of Public Health Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China
                [ 3 ] Department of Human Anatomy Histology and Embryology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science Center Xi'an Shaanxi China
                [ 4 ] School of Public Health Shaanxi University of Chinese Medicine Xianyang Shaanxi China
                [ 5 ] Xianyang Central Hospital Xianyang Shaanxi China
                [ 6 ] Department of Neurology The First Affiliated Hospital of Jinan University Guangzhou Guangdong China
                Author notes
                [*] [* ] Correspondence

                Jun Lyu, Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510632, Guangdong, China.

                Email: lyujun2019@ 123456163.com

                Anding Xu, Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510632, Guangdong Province, China.

                Email: tlil@ 123456jnu.edu.cn

                Article
                JEBM12373
                10.1111/jebm.12373
                7065247
                32086994
                2912111f-3687-433d-bc45-9fc0049d77cb
                © 2020 The Authors. Journal of Evidence‐Based Medicine published by Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 August 2019
                : 23 January 2020
                Page count
                Figures: 0, Tables: 1, Pages: 13, Words: 11943
                Funding
                Funded by: National Social Science Foundation of China
                Award ID: 16BGL183
                Categories
                Review
                Reviews
                Custom metadata
                2.0
                February 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.7 mode:remove_FC converted:11.03.2020

                Medicine
                big data,data mining,database,method,technology
                Medicine
                big data, data mining, database, method, technology

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