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Temporal information extraction from clinical text
2017
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
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In this paper, we present a method for temporal relation extraction from clinical narratives in French and in English. ...
Related Work Temporal information extraction from clinical texts has been the topic of several shared tasks over the past few years. ...
Introduction Temporal information extraction from electronic health records has become a subject of interest, driven by the need for medical staff to access medical information from a temporal perspective ...
doi:10.18653/v1/e17-2117
dblp:conf/eacl/FerretTNT17
fatcat:kke3464swzggxlycvuad6wbwta
A hybrid system for temporal information extraction from clinical text
2013
JAMIA Journal of the American Medical Informatics Association
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Objective To develop a comprehensive temporal information extraction system that can identify events, temporal expressions, and their temporal relations in clinical text. ...
This project was part of the 2012 i2b2 clinical natural language processing (NLP) challenge on temporal information extraction. ...
Institute (NHLBI), and by award number 1R13LM01141101 from the NLM. ...
doi:10.1136/amiajnl-2013-001635
pmid:23571849
pmcid:PMC3756274
fatcat:c2punx4abngdlp2mjveldyuriu
UtahBMI at SemEval-2016 Task 12: Extracting Temporal Information from Clinical Text
2016
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
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The 2016 Clinical TempEval continued the 2015 shared task on temporal information extraction with a new evaluation test set. ...
Acknowledgments We would like to thank the Mayo clinic and the 2016 Clinical TempEval challenge organizers for providing access to the clinical corpus, and arranging NLP shared task. ...
Conclusion Temporal information extraction and reasoning from clinical text remains a challenging task. ...
doi:10.18653/v1/s16-1195
dblp:conf/semeval/AbdulsalamVM16
fatcat:q3xtfniikzho5lymkeiutx7an4
Investigating the Challenges of Temporal Relation Extraction from Clinical Text
2018
Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis
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We explore to adapt the tree-based LSTM-RNN model proposed by Miwa and Bansal (2016) to temporal relation extraction from clinical text, obtaining a five point improvement over the best 2016 Clinical TempEval ...
tasks of event and time expressions but poorly in temporal relation extraction, showing a gap of around 0.25 point below human performance. ...
Up to now, there have been several attempts on tackling temporal relation extraction from clinical text mostly led by the Clinical TempEval challenges. ...
doi:10.18653/v1/w18-5607
dblp:conf/acl-louhi/GalvanOMI18
fatcat:ou2gb4gcl5crvarry5psyezq4e
TNorm: A Pattern Learning Approach for Temporal Expression Classification and Normalization from Chinese Narrative Clinical Texts (Preprint)
2019
JMIR Medical Informatics
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The goal of the study was to propose a novel approach for extracting and normalizing temporal expressions from Chinese narrative clinical text. ...
This study illustrates an automatic approach, TNorm, that extracts and normalizes temporal expression from Chinese narrative clinical texts. ...
Thus, extraction and normalization of temporal information from these unstructured texts is exceedingly valuable for clinical timeline construction as well as diagnosis procedure identification for clinical ...
doi:10.2196/17652
pmid:32716307
fatcat:3dvqvqev2rf2jopuvyf27yjlj4
Temporal reasoning over clinical text: the state of the art
2013
JAMIA Journal of the American Medical Informatics Association
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Scope We review the major applications of text-based temporal reasoning, describe the challenges for software systems handling temporal information in clinical text, and give an overview of the state of ...
Objectives To provide an overview of the problem of temporal reasoning over clinical text and to summarize the state of the art in clinical natural language processing for this task. ...
; (2) extraction of temporal information from natural language text; and (3) temporal inference over the extracted information. ...
doi:10.1136/amiajnl-2013-001760
pmid:23676245
pmcid:PMC3756277
fatcat:e4ehiljfcfekhlklclj2lbiebe
A pattern learning-based method for temporal expression extraction and normalization from multi-lingual heterogeneous clinical texts
2018
BMC Medical Informatics and Decision Making
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Though a variety of commonly used NLP tools are available for medical temporal information extraction, few work is satisfactory for multi-lingual heterogeneous clinical texts. ...
Methods: A novel method called TEER is proposed for both multi-lingual temporal expression extraction and normalization from various types of narrative clinical texts including clinical data requests, ...
A comprehensive system for extracting temporal information from clinical texts was proposed by Tang et al. [20] . ...
doi:10.1186/s12911-018-0595-9
pmid:29589563
pmcid:PMC5872502
fatcat:jjux5wwb4jfcxlz32jo6ndfpku
Current Development and Technology in the Information Extraction for Clinical Narrative Text
2015
International Journal of Computer Science and Application
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The information extractions from clinical narrative text are more complicated than those from other biomedical texts, such as books, articles, literature abstracts, and so on. ...
In this paper, we review recent published researches on the implication and technology of information extraction from free-text clinical narratives. ...
Typical Systems for Information Extraction from Clinical Narrative Text There are many software systems support information extraction from clinical text. ...
doi:10.12783/ijcsa.2015.0402.01
fatcat:4cch3i72jjbo5hvnbbssvwnnpi
Recognizing Temporal Information in Korean Clinical Narratives through Text Normalization
2011
Healthcare Informatics Research
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In this paper, we describe an approach that can be used to extract the temporal information found in Korean clinical narrative texts. ...
of human efforts were needed to deliver information from the text. ...
A number of approaches and systems have been developed to extract temporal information from natural language texts. Most of their work aimed to extract temporal information from the newswire text. ...
doi:10.4258/hir.2011.17.3.150
pmid:22084809
pmcid:PMC3212741
fatcat:g6v6bsf6tjfn5kfztqmedqgx7e
Temporal Relation Extraction in Clinical Texts
2022
ACM Computing Surveys
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Therefore, we propose a review of temporal relation extraction in clinical texts. ...
The publication of several studies on temporal relation extraction from clinical texts during the last decade and the realization of multiple shared tasks highlight the importance of this research theme ...
Temporal Relation Extraction Example In this section, we provide an example in Figure 1 to justify the benefit of extracting temporality from clinical texts. ...
doi:10.1145/3462475
fatcat:gfeitsdyungmvnfyowf6tjshee
CMedTEX: A Rule-based Temporal Expression Extraction and Normalization System for Chinese Clinical Notes
2017
AMIA Annual Symposium Proceedings
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The goal of this study was to analyze the challenges of temporal expression (TE) extraction and normalization in Chinese clinical notes by assessing the performance of a rule-based system developed by ...
Compared with HeidelTime for Chinese newswire text, our system is much better, indicating that it is necessary to develop a specific TE extraction and normalization system for Chinese clinical notes because ...
In the clinical domain, there also have been a few temporal information extraction systems. ...
pmid:28269878
pmcid:PMC5333232
fatcat:adqnh3vxezdqhont27rf2uscym
Recognition of Time Expressions in Spanish Electronic Health Records
2019
Zenodo
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Therefore, in this paper we propose a Temporal Tagger for identifying and normalizing time expressions appeared in Spanish clinical texts. ...
clinical texts, written in this particular language. ...
SUTime [16] [17], a pattern-based extraction annotator, is basically developed for retrieval of time information from English free texts. ...
doi:10.5281/zenodo.2871454
fatcat:2zv6yollz5d2bhjrqhty2y4eey
Extracting temporal constraints from clinical research eligibility criteria using conditional random fields
2011
AMIA Annual Symposium Proceedings
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In this paper, we present an ontology-based approach to extracting temporal information from clinical research eligibility criteria. ...
We manually annotated 150 free-text eligibility criteria using the temporal labels and trained a parser using Conditional Random Fields (CRFs) to automatically extract temporal expressions from eligibility ...
We thank Mary Regina Boland for her help on the evaluation of the temporal ontology. ...
pmid:22195142
pmcid:PMC3243135
fatcat:2i47bqpih5hkpgtelijqa35o3q
Task-Oriented Extraction of Temporal Information: The Case of Clinical Narratives
2006
Thirteenth International Symposium on Temporal Representation and Reasoning (TIME'06)
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Most recent work on temporal relation extraction from text has addressed text drawn from the newswire domain and has attempted to extract all temporal relational information, as specified by proposed temporal ...
about times of clinical investigations (X-rays, ultrasounds, etc.) from clinic letters. ...
Introduction While the task of extracting all the temporal information from a text is a worthwhile long term objective for natural language analysis, there may be many cases where extracting limited information ...
doi:10.1109/time.2006.27
dblp:conf/time/GaizauskasHHS06
fatcat:x7fjlgh7aze4phvw25wpcyjal4
A Text Structuring Method for Chinese Medical Text Based on Temporal Information
2018
International Journal of Environmental Research and Public Health
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This paper proposes a novel text structuring method to extract knowledge from EMR texts and reorganize them in chronological order according to the temporal information in the text. ...
Chinese Electronic Medical Records (EMRs) contains a large number of complex medical free text which includes a variety of information, such as temporal information, patients' symptoms and laboratory data ...
Extracting data from text is an important way to structure the text data. However, some information from data may be missed during the extraction process. ...
doi:10.3390/ijerph15030402
pmid:29495428
pmcid:PMC5876947
fatcat:dpdyclallfagpigy7qk3ixtfsi
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