[1]刘宏嘉,王静,黄宇亮,等.基于Web爬虫技术的电子病历信息聚合工具的开发及验证[J].中国医学物理学杂志,2021,38(11):1444-1448.[doi:DOI:10.3969/j.issn.1005-202X.2021.11.022]
 LIU Hongjia,WANG Jing,et al.Development and validation of a Web-crawler-based medical records information aggregation tool[J].Chinese Journal of Medical Physics,2021,38(11):1444-1448.[doi:DOI:10.3969/j.issn.1005-202X.2021.11.022]
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基于Web爬虫技术的电子病历信息聚合工具的开发及验证()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
38卷
期数:
2021年第11期
页码:
1444-1448
栏目:
医学人工智能
出版日期:
2021-11-26

文章信息/Info

Title:
Development and validation of a Web-crawler-based medical records information aggregation tool
文章编号:
1005-202X(2021)11-1444-05
作者:
刘宏嘉12王静3黄宇亮12李晨光12吴昊12马文君4曹文田4张艺宝12
1.北京大学医学部医学技术研究院, 北京 100191; 2.北京大学肿瘤医院暨北京市肿瘤防治研究所放疗科/恶性肿瘤发病机制及转化研究教育部重点实验室, 北京 100142; 3.浙江大学医学院附属邵逸夫医院, 浙江 杭州 310202; 4.北京大学物理学院, 北京 100871
Author(s):
LIU Hongjia1 2 WANG Jing3 HUANG Yuliang1 2 LI Chenguang1 2 WU Hao1 2 MA Wenjun4 CAO Wentian4 ZHANG Yibao1 2
1. Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China 2. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China 3. Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310202, China 4. School of Physics, Peking University, Beijing 100871, China
关键词:
网络爬虫自动分析大数据医院信息系统
Keywords:
Keywords: Web crawler automatic analysis big data hospital information system
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2021.11.022
文献标志码:
A
摘要:
目的:以放疗科的临床和科研工作需求为导向,开发和验证一种基于Web爬虫技术的电子病历信息聚合工具。方法:基于Selenium框架和Python编程语言,设计一种基于Web爬虫的病历信息聚合工具,并列举两个实际应用场景:回顾性研究中的数据准备工作以及聚合报告新入院患者的常规临床检查结果作为例子进行说明。测试该工具对临床工作流程的益处,比较自动化方法和手动方法的效率和准确性。结果:与人工方法相比,自动信息聚合工具表现出优秀的效率和准确性。对于第一个场景,自动化工具从3 541例患者中提取出110例放射性肺炎的病例,平均每例患者耗时54 s;而人工方法提取出相同数量的病例,平均每例患者耗时90 s。对于另一个例子,自动化方法平均每例患者耗时10 s,而人工方法平均每例患者耗时75 s。结论:本工作开发的工具可以在较低访问权限下实现临床和科研工作所需的数据检索、分类汇总等特殊功能,具有安全、高效、准确、跨平台、易拓展等优势。
Abstract:
Abstract: Objective To develop and validate a Web-crawler-based medical records information aggregation tool for the clinical and research practices in Department of Radiation Oncology. Methods Based on Selenium framework and Python programming language, a Web-crawler-based medical records information aggregation tool was designed. The benefits of the proposed tool for clinical workflow were analyzed under two scenarios, namely the data preparation for retrospective study and the aggregate report of routine clinical examination results of newly-admitted patients. Moreover, the efficiency and accuracy between automatic and manual methods were also compared. Results Compared with manual method, the automatic information aggregation tool had superior efficiency and accuracy. For the first scenario, automatic method identified 110 radiation pneumonia cases out of 3 541 cases at the time cost of about 54 s per case, while manual methods also identified the same number of radiation pneumonia cases but cost about 90 s per case. For the other scenario, automatic method cost about 10 s per case and manual method cost 75 s per case. Conclusion The Web-crawler-based medical records information aggregation tool can implement special functions such as data retrieval and subtotal for clinical and scientific researches under low access rights, with the advantages of security, efficiency, accuracy, cross-platform and easy-to-extend application.

相似文献/References:

[1]张春玲,宋明军,杜海涛,等.颅盖骨骨折CT图像的计算机自动分析研究[J].中国医学物理学杂志,2013,30(06):4537.[doi:10.3969/j.issn.1005-202X.2013.06.017]
[2]吴昊,刘杰,岳海振,等.基于Web的剂量体积直方图数据自动提取工具开发及验证[J].中国医学物理学杂志,2016,33(5):433.[doi:10.3969/j.issn.1005-202X.2016.05.001]
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[3]张俊,朱金汉,庄永东,等. 基于卷积神经网络CT/CBCT影像质量自动分析[J].中国医学物理学杂志,2018,35(5):557.[doi:DOI:10.3969/j.issn.1005-202X.2018.05.012]
 ZHANG Jun,ZHU Jinhan,ZHUANG Yongdong,et al. Automatic analysis of CT/CBCT image quality based on convolutional neural network[J].Chinese Journal of Medical Physics,2018,35(11):557.[doi:DOI:10.3969/j.issn.1005-202X.2018.05.012]

备注/Memo

备注/Memo:
【收稿日期】2021-05-19 【基金项目】北京市自然科学基金(Z210008);国家重点研发计划(2019YFF01014405);国家自然科学基金(11505012);北京大学肿瘤医院科学研究基金学科骨干项目(2021-1);中央高校基本科研业务费/北京大学临床医学+X青年专项(PKU2021LCXQ027);北大百度基金资助项目(2020BD029);北京大学医学部教育教学研究立项项目(2020YB34) 【作者简介】刘宏嘉,硕士,研究方向:医学物理,E-mail: stevendeliu@foxmail.com;王静,博士,研究方向:医学物理,E-mail: fwjing@zju.edu.cn(刘宏嘉和王静为共同第一作者) 【通信作者】张艺宝,博士,高级工程师,硕士生导师,研究方向:医学物理,E-mail: ybzhang66@163.com
更新日期/Last Update: 2021-11-27