教育部中医内科学重点实验室开启大数据科研创新模式

2020-09-03 王瑞芳 中国网

北京东直门医院作为北京中医药大学的第一临床医院,拥有丰富的中医临床资源,多年来积累了海量的中医药大数据,此次与海森健康联合成立实验室就是“希望利用大数据、人工智能技术,挖掘医院积累下来的海

北京东直门医院作为北京中医药大学的第一临床医院,拥有丰富的中医临床资源,多年来积累了海量的中医药大数据,此次与海森健康联合成立实验室就是“希望利用大数据、人工智能技术,挖掘医院积累下来的海量中医药数据的价值,助力临床研究。”东直门医院常务副院长商洪才在实验室揭牌仪式上强调。

2020年8月31日,海森健康联合教育部首个中医内科学重点实验室——北京中医药大学中医内科学教育部重点实验室(下称重点实验室)共同打造的“人工智能与中医药大数据联合实验室”(下称联合实验室),在北京中医药大学东直门医院(下称东直门医院)正式揭牌,成为将大数据与人工智能技术引进至中医药领域的一大里程碑。

东直门医院常务副院长、重点实验室主任商洪才、重点实验室副主任刘伟敬、重点实验室教授林生,海森健康科研业务负责人甘伟、商务总监李堂,北京中医药大学生命科学学院教授韩东燃、四川大学华西医院中国循证医学中心主任孙鑫,以及东直门医院男科主任李海松、妇科主任史云、肾病科主任周静威、心内科主任张立晶、脑科主任杨保林、信息中心副主任刘涓等临床科室负责人出席了揭牌仪式。

北京中医药大学中医内科学教育部重点实验室成立于2002年,是东直门医院的龙头实验室,其前身是由北京中医药大学东直门医院气血研究室,中医脑病研究室和部分基础实验室人员,于1999年联合建设成为“211工程”的学校级重点学科实验室,2002年被教育部批准为首个开展中医药基础和应用基础科学研究的重点实验室,同年被北京市教育委员会认定为重点实验室。

刘伟敬介绍,近三年来,北京中医药大学中医内科学教育部重点实验室共承担课题97项,其中承担国家重大课题3项、国家自然科学基金课题23项、省部级课题9项;发表SCI论文114篇,单篇最高影响因子近24分;2020年,实验室脑病研究团队、血管研究团队初评通过国家科技进步一等奖、二等奖各一项,是中医药领域名副其实的“科研大户”。

海森健康是嘉和美康集团成员企业,专注于提供医疗大数据、人工智能及互联网医疗的智慧医疗创新服务,具备强大的大数据、人工智能技术能力,并承袭集团十多年的医疗信息化积累。海森健康大数据科研平台是以智能医学数据中台为核心,通过整合院内各业务系统数据,并结合前瞻性课题数据库,对相关数据进行治理、融合及质控、建模等,为科研工作提供优质、可靠的数据资源。在此基础上,利用平台的人群筛选、人群管理、特征分析、可视化展示、统计分析、数据导出和权限管理等功能,即可轻松实现一站式科研工作模式,极大提高科研效率及整体研究质量。

中医药有着悠久的发展历史、丰富的实践经验和海量的文献,但其技术水平的增长,需要在临床试验中不断总结、摸索,经验极具个性化。此外,中医临床产生的大量诊疗数据,尤其是中西医诊疗的综合信息资源整体利用度不高,大量数据资源浪费,掣肘着中医药的发展。

对于这一点,商洪才有着清晰的认识。揭牌仪式上,他强调,东直门医院作为北京中医药大学的第一临床医院,拥有丰富的中医临床资源,多年来积累了海量的中医药大数据,此次与海森健康联合成立实验室就是“希望利用大数据、人工智能技术,挖掘医院积累下来的海量中医药数据的价值,助力临床研究。”

迫切的临床数据分析、处理需求背后,折射出的是医院在科研上不断暴露出的问题。以男科为例,该院男科主任李海松介绍,由于涉及到隐私,部分患者不愿意记录下自己详细的患病信息,一些数据在临床诊疗阶段就出现了缺失,到研究阶段的时候,“你要查某一类患者的详细信息,信息系统里经常查不到。”

在李海松看来,科研数据在临床阶段就要有针对性地进行收集,需要临床和科研形成一体化,“建设一个医疗和科研一体化的平台”成了以李海松为代表的众多科主任的共同心声。

利用大数据、人工智能技术能很好地解决这一痛点。甘伟介绍,依托大数据、人工智能技术打造的科研平台可以通过多层级自然语言处理体系,将复杂的病历文书及检查报告等文本数据转化成结构清晰的多维度科研数据项;并能根据数据清洗规则智能清洗数据,最大限度提高数据利用率。同时,在科研方式上,也能形成线上与线下的结合、联动,提升科研效率。

线上,主要基于大数据科研平台,实现对院内外全量数据的采集、处理及挖掘分析等,帮助科研人员快速确立研究方向、获取相关数据,并“一站式”完成目标人群建立、统计模型选择及结论汇总分析等步骤,大大缩短了科研周期,并提高了成果质量;线下服务则主要包括:研究方案设计,专病库搭建,统计咨询指导,数据治理服务,以及数据挖掘、建模等。

两者结合,实现海量真实诊疗数据在临床研究中的深度利用,以及研究成果对于临床决策的有效反哺,助力医院打造以专病库为核心的“临床-科研一体化”发展路径。

事实上,作为我国古代医学的精粹,中医药一直备受国家的高度重视:2016年《“健康中国2030”规划纲要》就提出,要强化中医药防治优势病种研究,推进中医药继承创新;2019年国务院办公厅发布的《关于促进中医药传承创新发展的意见》也强调,要促进中医药传承与开放创新发展;《中医药发展“十三五”规划》也强调了要加强中医药研究,推进理论与技术创新。在2020年抗击新冠疫情中,中医药更是发挥了至关重要的作用。

未来,联合实验室将整合东直门医院丰富的中医药临床大数据资源、北京中医药大学中医内科学教育部重点实验室雄厚的科研实力,以及海森健康强大的大数据与人工智能技术优势,围绕中医药大数据分析的诊断、治疗以及智能预测诊疗模型构建、真实世界研究等一系列课题展开深度合作,从而推动我国中医药的发展,让中医药惠及更多的民众,推动健康中国建设。

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    2021-11-09 湘雅科教

    已拜读,受益匪浅。

    0

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    2020-09-05 huagfeg
  4. [GetPortalCommentsPageByObjectIdResponse(id=1068464, encodeId=06701068464b1, content=已拜读,受益匪浅。, beContent=null, objectType=article, channel=null, level=null, likeNumber=72, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=6c905475903, createdName=湘雅科教, createdTime=Tue Nov 09 10:27:01 CST 2021, time=2021-11-09, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1285907, encodeId=ab1a128590ee1, content=<a href='/topic/show?id=77903209422' target=_blank style='color:#2F92EE;'>#创新#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=58, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=32094, encryptionId=77903209422, topicName=创新)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=512a199, createdName=lilianxiang, createdTime=Sat Sep 05 14:54:39 CST 2020, time=2020-09-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1398747, encodeId=d2f21398e472a, content=<a href='/topic/show?id=22fc5e61784' target=_blank style='color:#2F92EE;'>#教育部#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=72, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=57617, encryptionId=22fc5e61784, topicName=教育部)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=1dbc2500219, createdName=huagfeg, createdTime=Sat Sep 05 14:54:39 CST 2020, time=2020-09-05, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=882764, encodeId=7664882e64ac, content=好, beContent=null, objectType=article, channel=null, level=null, likeNumber=118, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20200903/79d0f015e6084e5ca462828ca002414e/27d5d6b264cb4eeebf7092dc1fb8eae8.jpg, createdBy=22155415237, createdName=ms7000000139248197, createdTime=Fri Sep 04 18:56:50 CST 2020, time=2020-09-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=882742, encodeId=d43e882e42e4, content=,, beContent=null, objectType=article, channel=null, level=null, likeNumber=136, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20200903/79d0f015e6084e5ca462828ca002414e/27d5d6b264cb4eeebf7092dc1fb8eae8.jpg, createdBy=22155415237, createdName=ms7000000139248197, createdTime=Fri Sep 04 18:50:19 CST 2020, time=2020-09-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1049772, encodeId=c0f61049e7240, content=中医中药,大多被人诋毁,不过williamhill asia 里总是客观公正的, beContent=null, objectType=article, channel=null, level=null, likeNumber=65, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=运动yd, createdTime=Fri Sep 04 02:54:39 CST 2020, time=2020-09-04, status=1, ipAttribution=)]
    2020-09-04 ms7000000139248197

    0

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    2020-09-04 ms7000000139248197

    0

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    2020-09-04 运动yd

    中医中药,大多被人诋毁,不过williamhill asia 里总是客观公正的

    0

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