人工智能技术的应用:罕见病临床决策系统的需求、现状与挑战
CSTR:
作者:
作者单位:

生物医学信息研究中心,上海市儿童医院,上海交通大学,上海市儿童医院,上海市儿童医院,上海市儿童医院,上海市儿童医院,上海市儿童医院

作者简介:

通讯作者:

中图分类号:

基金项目:

上海市科学技术委员会2018年度上海市优秀学术技术带头人计划(18XD1403200),上海儿童精准医学大数据工程技术研究中心项目,上海市科学技术委员会专项基金(17DZ22512000),上海市卫生计划生育委员会研究课题(2018ZHYL0223),上海市卫生计划生育委员会青年研究项目(20144Y0179).


Application of artificial intelligence technology: clinical demands, status and challenges of clinical decision support system for rare diseases
Author:
Affiliation:

Biomedical Informatics Research Center,Shanghai Children’s Hospital,Shanghai Jiao Tong University,Biomedical Informatics Research Center,Shanghai Children’s Hospital,Shanghai Jiao Tong University,Department of Child Healthcare,Shanghai Children’s Hospital,Shanghai Jiao Tong University,Biomedical Informatics Research Center,Shanghai Children’s Hospital,Shanghai Jiao Tong University,Biomedical Informatics Research Center,Shanghai Children’s Hospital,Shanghai Jiao Tong University,Biomedical Informatics Research Center,Shanghai Children’s Hospital,Shanghai Jiao Tong University

Fund Project:

Supported by Leading Scientist Plan of Shanghai Science and Technology Commission (18XD1403200), Project of Shanghai Big Data Engineering and Technology Research Center for Pediatric Precision Medicine, Special Fund from Shanghai Science and Technology Committee (17DZ22512000), Scientifc Research Project of Health and Family Planning Commision of Shanghai (2018ZHYL0223), and Scientifc Research Project for Young Scientists of Health and Family Planning Commision of Shanghai (20144Y0179).

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    罕见病的发病率极低,但其总体患病人数不少。罕见病引起的病变后果严重,对患者及其家庭和社会造成了沉重负担。虽然当前利用基因测序技术、临床决策支持系统结合人工智能技术辅助临床进行遗传病诊断的研究火热,但临床诊断罕见病仍是非常大的技术挑战。本文简要综述了罕见病临床决策系统,旨在分析人工智能技术在罕见病中的发展现状和挑战。

    Abstract:

    The incidence of rare diseases is extremely low, but the overall number of patients with rare diseases is quite large. The consequences of rare diseases are severe and impose a heavy burden on patients, their families and the entire society. Although there are many researches on gene sequencing technology and clinical decision support system (CDSS) combined with artificial intelligence technology to assist the diagnosis of rare diseases, the diagnosis of rare diseases remains a great challenge in clinical practice. In this paper, we briefly reviewed the CDSS for rare diseases, aiming to analyze the current technique status and challenges of artificial intelligence technology in rare diseases.

    参考文献
    相似文献
    引证文献
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2018-08-06
  • 最后修改日期:2018-08-15
  • 录用日期:2018-09-07
  • 在线发布日期: 2018-09-07
  • 出版日期:
文章二维码
重要通知
友情提醒: 近日发现论文正式见刊或网络首发后,有人冒充我刊编辑部名义给作者发邮件,要求添加微信,此系诈骗行为!可致电编辑部核实:021-81870792。
            《海军军医大学学报》编辑部
关闭