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完善垂体疾病数据库建设 开展高质量临床研究

王任直,  冯铭,  范阳华

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文章导航 > 协和医学杂志  > 2020 >  11(3): 339-342
王任直, 冯铭, 范阳华. 完善垂体疾病数据库建设 开展高质量临床研究[J]. 协和医学杂志, 2020, 11(3): 339-342. doi: 10.3969/j.issn.1674-9081.20200040
引用本文: 王任直, 冯铭, 范阳华. 完善垂体疾病数据库建设 开展高质量临床研究[J]. 协和医学杂志, 2020, 11(3): 339-342. doi: 10.3969/j.issn.1674-9081.20200040
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Ren-zhi WANG, Ming FENG, Yang-hua FAN. Improve the Database of Pituitary Diseases, Carry Out High Quality Clinical Research[J]. Medical Journal of Peking Union Medical College Hospital, 2020, 11(3): 339-342. doi: 10.3969/j.issn.1674-9081.20200040
Citation: Ren-zhi WANG, Ming FENG, Yang-hua FAN. Improve the Database of Pituitary Diseases, Carry Out High Quality Clinical Research[J]. Medical Journal of Peking Union Medical College Hospital, 2020, 11(3): 339-342. doi: 10.3969/j.issn.1674-9081.20200040
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完善垂体疾病数据库建设 开展高质量临床研究

doi: 10.3969/j.issn.1674-9081.20200040

  • 中国医学科学院 北京协和医学院 北京协和医院神经外科, 北京 100730

详细信息
    通讯作者:

    王任直 电话:010-69156074,E-mail:wangrz@126.com

  • 中图分类号: R651;R584

Improve the Database of Pituitary Diseases, Carry Out High Quality Clinical Research

  • Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

More Information
    Corresponding author: WANG Ren-zhi Tel: 86-10-69156074， E-mail: wangrz@126.com

    摘要
  • 摘要: 我国人口基数大、患者众多且复杂,但医疗资源分布不均衡,各级医疗机构对垂体疾病的诊治水平亦参差不齐,容易产生诊疗不规范现象甚至误诊、误治。随着医院信息化和互联网技术的发展,可对临床医疗过程中产生的海量数据进行清洗和整合,这为构建和完善垂体疾病数据库提供了可能。我们应充分利用人工智能技术、真实世界研究方法对数据进行深度挖掘、归纳和分析,并结合临床中遇到的问题开展相关临床研究,构建更高效、一致性更佳的临床诊疗辅助解决方案,指导临床医生制定更合理的诊疗决策,以期实现垂体疾病的个体化诊疗。
    Abstract: There are a large number of patients in China, but the distribution of medical resources is unbalanced. The diagnosis and treatment level of pituitary diseases in medical institutions is uneven, which makes this kind of disease easily misdiagnosed and improperly treated. With the development of hospital information technology and internet technology, a large number of clinical medical data can build and improve the database of pituitary diseases after data cleaning. With artificial intelligence technology and real world research methods, data are deeply mined, summarized, and analyzed. In view of problems encountered in clinical practice, we should carry out relevant clinical research, build a more efficient and consistent auxiliary solution to clinical diagnosis and treatment, guide clinicians to formulate more reasonable diagnosis and treatment strategies, and realize individualized diagnosis and treatment for pituitary diseases.
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    • 参考文献(20)
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出版历程
  • 收稿日期:  2020-02-21
  • 刊出日期:  2020-05-30

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