Evolution of semantic annotations (ELISA)

语义注释的演变 (ELISA)

• 批准号: 265240015
• 负责人: Professor Dr.-Ing. Erhard Rahm
• 金额: --
• 依托单位: Institut für Informatik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/265240015?language=en
• 关键词: Evolution; semantic; annotations; ELISA

The use of Knowledge Organization Systems (KOS) such as thesauri or ontologies in the medical field has shown great value to tackle semantic interoperability issues. In many cases, KOS are used to annotate real world objects such as electronic health records (EHR), case report forms (CRF) of clinical trials, genes or publications in order to make their semantics explicit for applications and tools. The dynamic nature of medical knowledge forces knowledge engineers to continuously revise the content of either KOSs or underlying data. These changes may directly impact the annotations associated with changed concepts or changed data. Hence, new KOS versions can invalidate previous annotations. Similarly, if the content of an annotated document is modified the existing annotation may become irrelevant. As a result, many annotations can lose their relevance and value thus impeding the intended use and exploitation of annotated data. The ELISA (Evolution of Semantic Annotations) project therefore will develop methods and tools for supporting the (semi-)automatic maintenance of semantic annotations affected by KOS or information evolution in order to keep annotations exploitable. The proposed approaches will be based on a comprehensive annotation model and make use of fine-grained information coming from KOS as well as information evolution to define a robust maintenance mechanism for preserving the validity of semantic annotations over time. The proposed framework will include different approaches to evolve or migrate annotations affected by changes, either by modifying annotations directly or an indirect way when annotations cannot directly be changed, e.g., in the case of encrypted EHRs. The ELISA approaches will be empirically evaluated using annotations between corpora of documents such as EHRs or CRFs and large biomedical KOS like SNOMED CT, NCI thesaurus and ICD-10. Expert-validated annotations will be available from real case studies in the Luxembourgish eSanté platform as well as the Leipzig Research Centre for Civilization Diseases (LIFE).

在医学领域中使用知识组织系统(KOS)，如叙词表或本体，已经显示出解决语义互操作性问题的巨大价值。在许多情况下，KOS被用来注释现实世界的对象，如电子健康记录(EHR)、临床试验的病例报告表(CRF)、基因或出版物，以便使它们的语义对于应用程序和工具是明确的。医学知识的动态性迫使知识工程师不断修改KOSS或基础数据的内容。这些更改可能会直接影响与更改的概念或更改的数据相关联的注释。因此，新的KOS版本可能会使以前的注释无效。同样，如果带注释的文档的内容被修改，则现有的注释可能变得无关紧要。因此，许多批注可能会失去其相关性和价值，从而阻碍批注数据的预期使用和利用。因此，EL ISA(语义注释演变)项目将开发方法和工具，以支持受KOS或信息演化影响的语义注释的(半自动)维护，以便保持注释的可利用性。所提出的方法将基于一个全面的标注模型，并利用来自KOS的细粒度信息以及信息演化来定义一种健壮的维护机制，以便随着时间的推移保持语义标注的有效性。所提出的框架将包括不同的方法来演变或迁移受改变影响的注释，或者通过直接修改注释，或者在注释不能直接改变时以间接方式，例如在加密的EHR的情况下。将使用EHR或CRF等文献语料库与SNOMED CT、NCI同义词词库和ICD-10等大型生物医学KO之间的注释对ELISA方法进行经验性评估。卢森堡eSanté平台以及莱比锡文明疾病研究中心(LIFE)的真实案例研究将提供经专家验证的注释。

项目成果

Towards a Multi-level Approach for the Maintenance of Semantic Annotations

维护语义注释的多层次方法

• DOI: 10.5220/0006230104010406
• 发表时间: 2017
• 作者: Silvio Domingos Cardoso;Chantal Reynaud-Delaître;Marcos Da Silveira;Ying-Chi Lin;Anika Groß;Erhard Rahm;Cédric Pruski
• 通讯作者: Cédric Pruski

Annotating Medical Forms Using UMLS

使用 UMLS 注释医疗表格

• DOI: 10.1007/978-3-319-21843-4_5
• 发表时间: 2015
• 作者: Victor Christen;Anika Groß;Julian Varghese;Martin Dugas;Erhard Rahm
• 通讯作者: Erhard Rahm

Evaluating Cross-lingual Semantic Annotation for Medical Forms

评估医疗表格的跨语言语义注释

• DOI: 10.5220/0008979901450155
• 发表时间: 2020
• 作者: Ying-Chi Lin;Victor Christen;Anika Groß;Toralf Kirsten;Silvio Domingos Cardoso;Cédric Pruski;Marcos Da Silveira;Erhard Rahm
• 通讯作者: Erhard Rahm

A Learning-Based Approach to Combine Medical Annotation Results - (Short Paper)

结合医学注释结果的基于学习的方法 -（短论文）

• DOI: 10.1007/978-3-030-06016-9_13
• 发表时间: 2018
• 作者: Victor Christen;Ying-Chi Lin;Anika Groß;Silvio Domingos Cardoso;Cédric Pruski;Marcos Da Silveira;Erhard Rahm
• 通讯作者: Erhard Rahm

Enhancing Cross-lingual Semantic Annotations using Deep Network Sentence Embeddings

使用深度网络句子嵌入增强跨语言语义注释

• DOI: 10.5220/0010256801880199
• 发表时间: 2021
• 作者: Ying-Chi Lin;Phillip Hoffmann;Erhard Rahm
• 通讯作者: Erhard Rahm