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SemEval-2015 Task 14: Analysis of Clinical Text

Noémie Elhadad, Sameer Pradhan, Sharon Gorman, Suresh Manandhar, Wendy Chapman, Guergana Savova
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes the SemEval-2014, Task 7 on the Analysis of Clinical Text and presents the evaluation results.  ...  It focused on two subtasks: (i) identification (Task A) and (ii) normalization (Task B  ...  This shared task was partially supported by Shared Annotated Resources (ShARe) project NIH 5R01GM090187 and Temporal Histories of Your Medical Events (THYME) project (NIH R01LM010090 and U54LM008748).  ... 
doi:10.18653/v1/s15-2051 dblp:conf/semeval/ElhadadPGMCS15 fatcat:wstngojzkjfexlizfo7hijr7qq

UTH-CCB: The Participation of the SemEval 2015 Challenge – Task 14

Jun Xu, Yaoyun Zhang, Jingqi Wang, Yonghui Wu, Min Jiang, Ergin Soysal, Hua Xu
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
The 2015 SemEval Shared Task 14, entitled "Analysis of Clinical Text", is to identify disorders and their modifiers from clinical text, which is an extension of the SemEval-2014 challenge.  ...  Conclusion In this paper, we described our participation in the SemEval-2015 challenge -Task 14 "Analysis of Clinical Text".  ... 
doi:10.18653/v1/s15-2052 dblp:conf/semeval/XuZWWJSX15 fatcat:ym2ga4hzrjhwfdrezswhzn5wqq

SemEval-2015 Task 4: TimeLine: Cross-Document Event Ordering

Anne-Lyse Minard, Manuela Speranza, Eneko Agirre, Itziar Aldabe, Marieke van Erp, Bernardo Magnini, German Rigau, Ruben Urizar
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes the outcomes of the TimeLine task (Cross-Document Event Ordering), that was organised within the Time and Space track of SemEval-2015.  ...  Four teams submitted the output of their systems to the four proposed subtracks for a total of 13 runs, the best of which obtained an F 1 -score of 7.85 in the main track (timeline creation from raw text  ...  The latter has been the topic of the three previous TempEval tasks within the SemEval challenges: Additionally, it has also been the focus of the 6th i2b2 NLP Challenge for clinical records (Sun et al  ... 
doi:10.18653/v1/s15-2132 dblp:conf/semeval/MinardSAAEMRU15 fatcat:cgtsbrftljbrhjp6rplt6hm4i4

TeamHCMUS: Analysis of Clinical Text

Nghia Huynh, Quoc Ho
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
We developed a system to participate in shared tasks on the analyzing clinical text. Our system approaches are both machine learning-based and rule-based.  ...  The evaluation on the test data showed that our system achieved the F-score of 0.656 (0.685 in case of relaxed score) for Task 1 and the F*WA of 0.576 for Task 2A and the F*WA of 0.671 for Task 2B.  ...  ., 2013 ), SemEval 2014 (Sameer Pradhan et al., 2014 , and SemEval 2015. In Section 2.1 we presented three representable forms of disorder in the clinical text.  ... 
doi:10.18653/v1/s15-2063 dblp:conf/semeval/HuynhH15 fatcat:onsv3wtzpffz5mfvbvlwv6vsn4

SemEval-2014 Task 7: Analysis of Clinical Text

Sameer Pradhan, Noémie Elhadad, Wendy Chapman, Suresh Manandhar, Guergana Savova
2014 Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)  
We describe two tasks-named entity recognition (Task 1) and template slot filling (Task 2)-for clinical texts. The tasks leverage annotations from the ShARe corpus, which con-  ...  We greatly appreciate the hard work of our program committee members and the ShARe annotators.  ...  The SemEval-2015 Task 14, Analysis of Clinical Text is the newest iteration in a series of community challenges organized around the tasks of named entity recognition for clinical texts.  ... 
doi:10.3115/v1/s14-2007 dblp:conf/semeval/PradhanECMS14 fatcat:7geisim4qjhk7m2srmip5hxq6u

Text Mining and Big Data Analytics for Retrospective Analysis of Clinical Texts from Outpatient Care

Svetla Boytcheva, Galia Angelova, Zhivko Angelov, Dimitar Tcharaktchiev
2015 Cybernetics and Information Technologies  
This paper presents the results of an on-going research project for knowledge extraction from large corpora of clinical narratives in Bulgarian language, approximately 100 million of outpatient care notes  ...  Entities with numerical values are mined in the free text and the extracted information is stored in a structured format.  ...  The annotation tasks related to competitions like i2b2 and SemEval [5] consolidate the efforts for the development of adequate linguistic resources.  ... 
doi:10.1515/cait-2015-0055 fatcat:2u2hkdnfnbf6zpsmwmhv3dib6e

ezDI: A Supervised NLP System for Clinical Narrative Analysis

Parth Pathak, Pinal Patel, Vishal Panchal, Sagar Soni, Kinjal Dani, Amrish Patel, Narayan Choudhary
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes the approach used by ezDI at the SemEval 2015 Task-14: "Analysis of Clinical Text". The task was divided into two embedded tasks.  ...  Task-1 required determining disorder boundaries (including the discontiguous ones) from a given set of clinical notes and normalizing the disorders by assigning a unique CUI from the UMLS/SNOMEDCT 1 .  ...  Task-14 of SemEval 2015 on 1 http://www.nlm.nih.gov/research/umls/ "analysis of clinical text" addresses the same concern.  ... 
doi:10.18653/v1/s15-2071 dblp:conf/semeval/PathakPPSDPC15 fatcat:37zjonwd65bfzccv4eczwqswgy

Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets

Denis Newman-Griffis, Guy Divita, Bart Desmet, Ayah Zirikly, Carolyn P Rosé, Eric Fosler-Lussier
2020 JAMIA Journal of the American Medical Informatics Association  
Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis.  ...  of ambiguity in clinical text.  ...  SemEval-2015 Task 14 of the SemEval-2015 competition investigated clinical text analysis using the ShARe corpus, which consists of 531 clinical documents from the MIMIC (Medical Information Mart for Intensive  ... 
doi:10.1093/jamia/ocaa269 pmid:33319905 pmcid:PMC7936394 fatcat:pgnuvrlv7rdqbgstmepayzafie

What is SemEval evaluating? A Systematic Analysis of Evaluation Campaigns in NLP [article]

Oskar Wysocki, Malina Florea, Andre Freitas
2020 arXiv   pre-print
This paper provides a systematic quantitative analysis of SemEval aiming to evidence the patterns of the contributions behind SemEval.  ...  By understanding the distribution of task types, metrics, architectures, participation and citations over time we aim to answer the question on what is being evaluated by SemEval.  ...  The analysis, which provides a detailed breakdown of 96 tasks in the period between 2012-2019, provided quantitative evidence that: (i) SemEval has a significant impact in the overall NLP community, (ii  ... 
arXiv:2005.14299v1 fatcat:bj42pwboazgjzejeaqk2xipfwi

Enhancing Clinical Concept Extraction with Contextual Embedding [article]

Yuqi Si, Jingqi Wang, Hua Xu, Kirk Roberts
2019 arXiv   pre-print
and SemEval 2015.  ...  Contextual embeddings pre-trained on a large clinical corpus achieves new state-of-the-art performances across all concept extraction tasks.  ...  National Library of Medicine, National Institutes of Health (NIH), under award R00LM012104, as well as the Cancer Prevention Research Institute of Texas (CPRIT), under awards RP170668 and RR180012.  ... 
arXiv:1902.08691v3 fatcat:zwy4xfq5bjbelhuvl7hu6jdw54

A Study of Neural Word Embeddings for Named Entity Recognition in Clinical Text

Yonghui Wu, Jun Xu, Min Jiang, Yaoyun Zhang, Hua Xu
2015 AMIA Annual Symposium Proceedings  
Clinical Named Entity Recognition (NER) is a critical task for extracting important patient information from clinical text to support clinical and translational research.  ...  Further analysis found that the neural word embeddings captured a wide range of semantic relations, which could be discretized into distributed word representations to benefit the clinical NER system.  ...  We would like to thank the 2010 i2b2/VA challenge organizers and the 2014 SemEval challenge organizers for the development of the corpora used in this study.  ... 
pmid:26958273 pmcid:PMC4765694 fatcat:ghdvzqwgrbcvhfw2ifaruisv5m

UtahPOET: Disorder Mention Identification and Context Slot Filling with Cognitive Inspiration

Kristina Doing-Harris, Sean Igo, Jianlin Shi, John Hurdle
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
We describe the performance of UtahPOET on SemEval 2015 Task 14. UtahPOET is a cognitively inspired system designed to extract semantic content from general clinical texts.  ...  We find that our system performs much better on the context slot-filling aspects of Tasks 2A and 2B than the disorder CUI mapping of Tasks 1 and 2B or the body location CUI mapping of Task 2B.  ...  Acknowledgments We are grateful for the support of the National Library of Medicine grant R01LM010981.  ... 
doi:10.18653/v1/s15-2069 dblp:conf/semeval/Doing-HarrisISH15 fatcat:iqyvjbijxnf2tgyyaifex5r3f4

LIST-LUX: Disorder Identification from Clinical Texts

Asma Ben Abacha, Aikaterini Karanasiou, Yassine Mrabet, Julio Cesar Dos Reis
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes our participation in task 14 of SemEval 2015.  ...  This task focuses on the analysis of clinical texts and includes: (i) the recognition of the span of a disorder mention and (ii) its normalization to a unique concept identifier in the UMLS/SNOMED-CT terminology  ...  We also want to acknowledge the efforts of the task organizers.  ... 
doi:10.18653/v1/s15-2074 dblp:conf/semeval/AbachaKMR15 fatcat:kfrm7mtb3fdkhjvignpchh4sem

IHS-RD-Belarus: Identification and Normalization of Disorder Concepts in Clinical Notes

Maryna Chernyshevich, Vadim Stankevitch
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
This paper describes clinical disorder recognition and encoding system submitted by IHS R&D Belarus team at the SemEval-2015 shared task related to analysis of clinical texts.  ...  The combined score for whole task is 0.690 (rank 17 out of 40 submissions).  ...  Conclusion In this paper, we presented a clinical analysis system designed for participation in Task 1a of the SemEval 2015 Task 14 challenge.  ... 
doi:10.18653/v1/s15-2065 dblp:conf/semeval/ChernyshevichS15 fatcat:lkc4dzgzh5ewdfzhkjkkufbdqi

A Hybrid Approach For Automatic Disability Annotation

Iakes Goenaga, Aitziber Atutxa, Koldo Gojenola, Arantza Casillas, Arantza Díaz de Ilarraza, Nerea Ezeiza, Maite Oronoz, Alicia Pérez, Olatz Perez-de-Viñaspre
2018 Annual Conference of the Spanish Society for Natural Language Processing  
The evaluation of the task is divided in two sub-tasks; one corresponding to the detection of English entities and the other to Spanish entities.  ...  The aim of this paper is to present the work pursued by the IXA group in the DIANN-Ibereval 2018 task.  ...  -The Basque Government (projects DETEAMI: 2014111003, ELKAROLA:KK-2015/00098).  ... 
dblp:conf/sepln/GoenagaAGCIEOPP18 fatcat:meliyo5zzjev5ld23t7e67xjea
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