CEUR workshop proceedings最新文献_第4页

Towards Automatic Generation of Portions of Scientific Papers for Large Multi-Institutional Collaborations Based on Semantic Metadata. 基于语义元数据的大型多机构协作科学论文部分自动生成研究。

CEUR workshop proceedings Pub Date : 2017-10-01

MiHyun Jang, Tejal Patted, Yolanda Gil, Daniel Garijo, Varun Ratnakar, Jie Ji, Prince Wang, Aggie McMahon, Paul M Thompson, Neda Jahanshad

引用次数: 0

UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection. 2017年CLEF风险试点任务:早期抑郁症检测的线性和循环模型。

CEUR workshop proceedings Pub Date : 2017-09-01 Epub Date: 2017-07-13

Farig Sadeque, Dongfang Xu, Steven Bethard

引用次数: 0

Clinical Information Extraction at the CLEF eHealth Evaluation lab 2016. CLEF健康评估实验室临床信息提取2016。

CEUR workshop proceedings Pub Date : 2016-09-01

Aurélie Névéol, K Bretonnel Cohen, Cyril Grouin, Thierry Hamon, Thomas Lavergne, Liadh Kelly, Lorraine Goeuriot, Grégoire Rey, Aude Robert, Xavier Tannier, Pierre Zweigenbaum

{"title":"Clinical Information Extraction at the CLEF eHealth Evaluation lab 2016.","authors":"Aurélie Névéol, K Bretonnel Cohen, Cyril Grouin, Thierry Hamon, Thomas Lavergne, Liadh Kelly, Lorraine Goeuriot, Grégoire Rey, Aude Robert, Xavier Tannier, Pierre Zweigenbaum","doi":"","DOIUrl":"","url":null,"abstract":"This paper reports on Task 2 of the 2016 CLEF eHealth evaluation lab which extended the previous information extraction tasks of ShARe/CLEF eHealth evaluation labs. The task continued with named entity recognition and normalization in French narratives, as offered in CLEF eHealth 2015. Named entity recognition involved ten types of entities including disorders that were defined according to Semantic Groups in the Unified Medical Language System® (UMLS®), which was also used for normalizing the entities. In addition, we introduced a large-scale classification task in French death certificates, which consisted of extracting causes of death as coded in the International Classification of Diseases, tenth revision (ICD10). Participant systems were evaluated against a blind reference standard of 832 titles of scientific articles indexed in MEDLINE, 4 drug monographs published by the European Medicines Agency (EMEA) and 27,850 death certificates using Precision, Recall and F-measure. In total, seven teams participated, including five in the entity recognition and normalization task, and five in the death certificate coding task. Three teams submitted their systems to our newly offered reproducibility track. For entity recognition, the highest performance was achieved on the EMEA corpus, with an overall F-measure of 0.702 for plain entities recognition and 0.529 for normalized entity recognition. For entity normalization, the highest performance was achieved on the MEDLINE corpus, with an overall F-measure of 0.552. For death certificate coding, the highest performance was 0.848 F-measure.","PeriodicalId":72554,"journal":{"name":"CEUR workshop proceedings","volume":"1609 ","pages":"28-42"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5756095/pdf/nihms921614.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35715159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying Missing Hierarchical Relations in SNOMED CT from Logical Definitions Based on the Lexical Features of Concept Names. 基于概念名称词法特征的逻辑定义中缺失层次关系识别。

CEUR workshop proceedings Pub Date : 2016-08-01

Olivier Bodenreider

引用次数: 0

Adding evidence type representation to DIDEO. 向DIDEO添加证据类型表示。

CEUR workshop proceedings Pub Date : 2016-08-01

Mathias Brochhausen, Philip E Empey, Jodi Schneider, William R Hogan, Richard D Boyce

引用次数: 0

Scalable Text Mining Assisted Curation of Post-Translationally Modified Proteoforms in the Protein Ontology. 可扩展的文本挖掘辅助管理翻译后修改的蛋白质本体中的蛋白质形式。

CEUR workshop proceedings Pub Date : 2016-08-01 Epub Date: 2016-11-29

Karen E Ross, Darren A Natale, Cecilia Arighi, Sheng-Chih Chen, Hongzhan Huang, Gang Li, Jia Ren, Michael Wang, K Vijay-Shanker, Cathy H Wu

{"title":"Scalable Text Mining Assisted Curation of Post-Translationally Modified Proteoforms in the Protein Ontology.","authors":"Karen E Ross, Darren A Natale, Cecilia Arighi, Sheng-Chih Chen, Hongzhan Huang, Gang Li, Jia Ren, Michael Wang, K Vijay-Shanker, Cathy H Wu","doi":"","DOIUrl":"","url":null,"abstract":"The Protein Ontology (PRO) defines protein classes and their interrelationships from the family to the protein form (proteoform) level within and across species. One of the unique contributions of PRO is its representation of post-translationally modified (PTM) proteoforms. However, progress in adding PTM proteoform classes to PRO has been relatively slow due to the extensive manual curation effort required. Here we report an automated pipeline for creation of PTM proteoform classes that leverages two phosphorylation-focused text mining tools (RLIMS-P, which detects mentions of kinases, substrates, and phosphorylation sites, and eFIP, which detects phosphorylation-dependent protein-protein interactions (PPIs)) and our integrated PTM database, iPTMnet. By applying this pipeline, we obtained a set of ~820 substrate-site pairs that are suitable for automated PRO term generation with literature-based evidence attribution. Inclusion of these terms in PRO will increase PRO coverage of species-specific PTM proteoforms by 50%. Many of these new proteoforms also have associated kinase and/or PPI information. Finally, we show a phosphorylation network for the human and mouse peptidyl-prolyl cis-trans isomerase (PIN1/Pin1) derived from our dataset that demonstrates the biological complexity of the information we have extracted. Our approach addresses scalability in PRO curation and will be further expanded to advance PRO representation of phosphorylated proteoforms.","PeriodicalId":72554,"journal":{"name":"CEUR workshop proceedings","volume":"1747 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504912/pdf/nihms868567.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35169500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Qualitative causal analyses of biosimulation models. 生物模拟模型的定性因果分析。

CEUR workshop proceedings Pub Date : 2016-08-01 Epub Date: 2016-11-29

Maxwell L Neal, John H Gennari, Daniel L Cook

{"title":"Qualitative causal analyses of biosimulation models.","authors":"Maxwell L Neal, John H Gennari, Daniel L Cook","doi":"","DOIUrl":"","url":null,"abstract":"We describe an approach for performing qualitative, systems-level causal analyses on biosimulation models that leverages semantics-based modeling formats, formal ontology, and automated inference. The approach allows users to quickly investigate how a qualitative perturbation to an element within a model's network (an increment or decrement) propagates throughout the modeled system. To support such analyses, we must interpret and annotate the semantics of the models, including both the physical properties modeled and the dependencies that relate them. We build from prior work understanding the semantics of biological properties, but here, we focus on the semantics for dependencies, which provide the critical knowledge necessary for causal analysis of biosimulation models. We describe augmentations to the Ontology of Physics for Biology, via OWL axioms and SWRL rules, and demonstrate that a reasoner can then infer how an annotated model's physical properties influence each other in a qualitative sense. Our goal is to provide researchers with a tool that helps bring the systems-level network dynamics of biosimulation models into perspective, thus facilitating model development, testing, and application.","PeriodicalId":72554,"journal":{"name":"CEUR workshop proceedings","volume":"1747 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5551042/pdf/nihms890699.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35315735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

OOSTT: a Resource for Analyzing the Organizational Structures of Trauma Centers and Trauma Systems. OOSTT：分析创伤中心和创伤系统组织结构的资源。

CEUR workshop proceedings Pub Date : 2016-08-01

Joseph Utecht, John Judkins, J Neil Otte, Terra Colvin, Nicholas Rogers, Robert Rose, Maria Alvi, Amanda Hicks, Jane Ball, Stephen M Bowman, Robert T Maxson, Rosemary Nabaweesi, Rohit Pradhan, Nels D Sanddal, M Eduard Tudoreanu, Robert J Winchell, Mathias Brochhausen

{"title":"OOSTT: a Resource for Analyzing the Organizational Structures of Trauma Centers and Trauma Systems.","authors":"Joseph Utecht, John Judkins, J Neil Otte, Terra Colvin, Nicholas Rogers, Robert Rose, Maria Alvi, Amanda Hicks, Jane Ball, Stephen M Bowman, Robert T Maxson, Rosemary Nabaweesi, Rohit Pradhan, Nels D Sanddal, M Eduard Tudoreanu, Robert J Winchell, Mathias Brochhausen","doi":"","DOIUrl":"","url":null,"abstract":"Organizational structures of healthcare organizations has increasingly become a focus of medical research. In the CAFÉ project we aim to provide a web-service enabling ontology-driven comparison of the organizational characteristics of trauma centers and trauma systems. Trauma remains one of the biggest challenges to healthcare systems worldwide. Research has demonstrated that coordinated efforts like trauma systems and trauma centers are key components of addressing this challenge. Evaluation and comparison of these organizations is essential. However, this research challenge is frequently compounded by the lack of a shared terminology and the lack of effective information technology solutions for assessing and comparing these organizations. In this paper we present the Ontology of Organizational Structures of Trauma systems and Trauma centers (OOSTT) that provides the ontological foundation to CAFÉ's web-based questionnaire infrastructure. We present the usage of the ontology in relation to the questionnaire and provide the methods that were used to create the ontology.","PeriodicalId":72554,"journal":{"name":"CEUR workshop proceedings","volume":"1747 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140195269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measurement Error and Causal Discovery. 测量误差和因果发现。

CEUR workshop proceedings Pub Date : 2016-06-01 Epub Date: 2017-02-08

Richard Scheines, Joseph Ramsey

引用次数: 0

Investigating Term Reuse and Overlap in Biomedical Ontologies. 研究生物医学本体中的术语重用和重叠。

CEUR workshop proceedings Pub Date : 2015-07-01 Epub Date: 2015-11-18

Maulik R Kamdar, Tania Tudorache, Mark A Musen

引用次数: 0