• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems.LORD:一种表型-基因型语义集成生物医学数据工具,用于支持健康信息系统中的罕见病诊断编码。
AMIA Annu Symp Proc. 2015 Nov 5;2015:434-40. eCollection 2015.
2
HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.HPO2Vec+:利用异构知识资源丰富人类表型本体的节点嵌入。
J Biomed Inform. 2019 Aug;96:103246. doi: 10.1016/j.jbi.2019.103246. Epub 2019 Jun 27.
3
Rare diseases in ICD11: making rare diseases visible in health information systems through appropriate coding.《国际疾病分类第11版》中的罕见病:通过适当编码使罕见病在健康信息系统中得以显现
Orphanet J Rare Dis. 2015 Mar 26;10:35. doi: 10.1186/s13023-015-0251-8.
4
Construction of the integrated multicentre discharge summary database.综合多中心出院小结数据库的构建。
Stud Health Technol Inform. 2013;192:1064.
5
Isosemantic rendering of clinical information using formal ontologies and RDF.使用形式本体和RDF对临床信息进行等语义渲染。
Stud Health Technol Inform. 2013;192:1085.
6
Meeting Patients' Right to the Correct Diagnosis: Ongoing International Initiatives on Undiagnosed Rare Diseases and Ethical and Social Issues.满足患者获得正确诊断的权利:罕见病未确诊问题的国际持续行动和伦理社会问题。
Int J Environ Res Public Health. 2018 Sep 21;15(10):2072. doi: 10.3390/ijerph15102072.
7
Leveraging terminological resources for mapping between rare disease information sources.利用术语资源在罕见病信息源之间进行映射。
Stud Health Technol Inform. 2013;192:529-33.
8
[Orphanet and its consortium: where to find expert-validated information on rare diseases].[欧洲罕见病组织及其联盟:获取罕见病专家验证信息的途径]
Rev Neurol (Paris). 2013 Feb;169 Suppl 1:S3-8. doi: 10.1016/S0035-3787(13)70052-3.
9
Semantic enrichment of medical forms - semi-automated coding of ODM-elements via web services.医学表单的语义丰富——通过网络服务对ODM元素进行半自动编码。
Stud Health Technol Inform. 2012;180:1102-4.
10
Rare disease knowledge enrichment through a data-driven approach.通过数据驱动的方法丰富罕见病知识。
BMC Med Inform Decis Mak. 2019 Feb 14;19(1):32. doi: 10.1186/s12911-019-0752-9.

引用本文的文献

1
Drug repositioning model based on knowledge graph embedding.基于知识图谱嵌入的药物重新定位模型。
Sci Rep. 2025 Mar 25;15(1):10298. doi: 10.1038/s41598-025-95372-5.
2
What incentives increase data sharing in health and medical research? A systematic review.哪些激励措施能促进健康与医学研究中的数据共享?一项系统综述。
Res Integr Peer Rev. 2017 May 5;2:4. doi: 10.1186/s41073-017-0028-9. eCollection 2017.
3
Drugs for rare disorders.用于罕见疾病的药物。
Br J Clin Pharmacol. 2017 Aug;83(8):1607-1613. doi: 10.1111/bcp.13331. Epub 2017 Jun 27.
4
Management of rare diseases of the Head, Neck and Teeth: results of a French population-based prospective 8-year study.头、颈和牙齿罕见病的管理:一项基于法国人群的8年前瞻性研究结果
Orphanet J Rare Dis. 2017 May 19;12(1):94. doi: 10.1186/s13023-017-0650-0.

本文引用的文献

1
Evaluation of the performance of open-source RDBMS and triplestores for storing medical data over a web service.评估用于通过网络服务存储医学数据的开源关系数据库管理系统(RDBMS)和三元组存储的性能。
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4499-502. doi: 10.1109/EMBC.2014.6944623.
2
Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.《疾病本体论2015年更新:一个通过疾病数据连接生物医学知识的经过扩展和更新的人类疾病数据库》
Nucleic Acids Res. 2015 Jan;43(Database issue):D1071-8. doi: 10.1093/nar/gku1011. Epub 2014 Oct 27.
3
BioPortal as a Dataset of Linked Biomedical Ontologies and Terminologies in RDF.BioPortal作为RDF格式的链接生物医学本体和术语数据集。
Semant Web. 2013;4(3):277-284.
4
A methodology for a minimum data set for rare diseases to support national centers of excellence for healthcare and research.一种用于罕见病的最小数据集的方法,以支持国家医疗保健和研究卓越中心。
J Am Med Inform Assoc. 2015 Jan;22(1):76-85. doi: 10.1136/amiajnl-2014-002794. Epub 2014 Jul 18.
5
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.人类表型本体论项目:通过表型数据将分子生物学和疾病联系起来。
Nucleic Acids Res. 2014 Jan;42(Database issue):D966-74. doi: 10.1093/nar/gkt1026. Epub 2013 Nov 11.
6
An innovative portal for rare genetic diseases research: the semantic Diseasecard.用于罕见遗传疾病研究的创新门户:语义疾病卡片。
J Biomed Inform. 2013 Dec;46(6):1108-15. doi: 10.1016/j.jbi.2013.08.006. Epub 2013 Aug 21.
7
Interoperability in clinical research: from metadata registries to semantically annotated CDISC ODM.临床研究中的互操作性:从元数据注册库到语义注释的CDISC ODM
Stud Health Technol Inform. 2012;180:564-8.
8
Rare diseases knowledge management: the contribution of proximity measurements in OntoOrpha and OMIM.罕见病知识管理:OntoOrpha和OMIM中邻近度测量的贡献。
Stud Health Technol Inform. 2012;180:88-92.
9
[ICD-10 adaptation of 15 Agency for Healthcare Research and Quality patient safety indicators].[医疗保健研究与质量局15项患者安全指标的国际疾病分类第十版改编版]
Rev Epidemiol Sante Publique. 2011 Oct;59(5):341-50. doi: 10.1016/j.respe.2011.04.004. Epub 2011 Sep 6.
10
Health multi-terminology portal: a semantic added-value for patient safety.健康多术语门户:对患者安全的语义附加值。
Stud Health Technol Inform. 2011;166:129-38.

LORD:一种表型-基因型语义集成生物医学数据工具,用于支持健康信息系统中的罕见病诊断编码。

LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems.

作者信息

Choquet Remy, Maaroufi Meriem, Fonjallaz Yannick, de Carrara Albane, Vandenbussche Pierre-Yves, Dhombres Ferdinand, Landais Paul

机构信息

Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, APHP, F-75015, Paris, France; INSERM, U1142, LIMICS, F-75006, Paris, France.

Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, APHP, F-75015, Paris, France.

出版信息

AMIA Annu Symp Proc. 2015 Nov 5;2015:434-40. eCollection 2015.

PMID:26958175
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4765596/
Abstract

Characterizing a rare disease diagnosis for a given patient is often made through expert's networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different thesaurus such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8,400 rare diseases linked to more than 14,500 signs and 3,270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine.

摘要

对于特定患者的罕见病诊断通常是通过专家网络来进行的。这是一项复杂的任务,可能会随着疾病的自然史和科学知识的发展而演变。大多数罕见病都有遗传原因,测序技术的最新进展每年都有助于发现许多新疾病。罕见病领域的诊断编码需要汇总来自多个知识库的数据,以便为临床医生提供一个从可能的诊断到临床症状(表型)和已知基因突变(基因型)的全局信息空间。如今,编码活动的主要障碍是缺乏对分散在不同词库(如孤儿病数据库、在线人类孟德尔遗传数据库或人类表型本体)中的此类信息的整合。我们开发的罕见病链接开放数据(LORD)门户网站首次尝试填补这一空白,它提供了8400种罕见病与14500多种症状和3270个基因之间的综合视图。该应用程序提供了一个浏览功能,用于浏览疾病、症状和基因之间的关系,以及一些应用程序编程接口,以帮助其在日常健康信息系统中进行集成。