| 可计算的临床证据综合:方法与进展 |
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| 引用本文： | 可计算的临床证据综合:方法与进展.可计算的临床证据综合:方法与进展[J].首都医学院学报,2022,43(4):576-583. |
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| 作者姓名： | 可计算的临床证据综合:方法与进展 |
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| 作者单位： | 1.北京大学医学部医学技术研究院,北京 100191;2.北京大学健康医疗大数据国家研究院,北京 100191;3.北京大学医学部公共卫生学院,北京 100191 |
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| 基金项目： | 国家自然科学基金面上项目(72074006),中国科协青年人才托举工程项目(2017QNRC001),北京大学医学部人才启动经费项目(BMU2021YJ008)。 |
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| 摘 要： | 医学出版物的快速增长,医疗数据的不断增加,为进行快速医学证据综合带来了前所未有的挑战。近年来,如何跟上海量医学证据的发展,并将其转化为临床实践是一个迫切需要解决的问题。充分利用结构化医学数据库,直接利用结构化数据促进医学证据合成已成为临床证据综合的一大趋势,尤其是在新型冠状病毒肺炎(COVID-19,以下简称新冠肺炎)疫情严峻的形势下,通过将人读的以PDF和HTML为主要格式的医学证据转化为机器可读的格式,构建医学知识图谱,服务国内医生快速了解医学研究进展,对于开展快速证据综合,支持循证临床决策具有十分重要的意义。本文介绍了当前针对系统综述和临床试验开展可计算证据综合的研究现状,并通过案例分析来明确可计算证据综合的实现框架和未来发展方向。
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| 关 键 词： | 可计算 证据综合 随机对照试验 系统综述 |
| 收稿时间： | 2022-03-21 |
Computable clinical evidence synthesis:a literature review |
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| Bai Yongmei,Du Jian.Computable clinical evidence synthesis:a literature review[J].Journal of Capital University of Medical Sciences,2022,43(4):576-583. |
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| Authors: | Bai Yongmei Du Jian |
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| Affiliation: | 1. Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, China;2. National Institute of Health Data Science, Peking University, Beijing 100191, China;3. School of Public Health, Peking University, Beijing 100191, China |
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| Abstract: | The rapid growth of medical publications and the increasing medical data have brought unprecedented difficulties for rapid clinical evidence synthesis. In recent years, how to keep up with the development of massive medical evidence and convert it into clinical practice has become an urgent problem to be solved. At present, the method of making full use of structured medical database and directly using structured data to promote the synthesis of medical evidence has become a major trend in clinical evidence synthesis. By converting human-readable medical evidence in PDF and HTML formats into machine-readable format, we can construct a graph of medical knowledge to help domestic doctors to quickly understand the medical research progress and carry out evidence synthesis to support evidence-based clinical decision-making. We introduced the current research status of computable evidence synthesis for system review and clinical trials and clarified the implementation framework and future development direction of computable evidence synthesis through case analysis. |
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| Keywords: | computable evidence synthesis randomized controlled trial(RCT) systematic review |
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