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1
Moonstone: a novel natural language processing system for inferring social risk from clinical narratives.
In: Journal of biomedical semantics, vol 10, iss 1 (2019)
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2
Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data
Conway, Mike; Hu, Mengke; Chapman, Wendy W.. - : Georg Thieme Verlag KG, 2019
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3
Overview of the ShARe/CLEF eHealth evaluation lab 2014
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015)
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4
Overview of the ShARe/CLEF eHealth evaluation lab 2014
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2015)
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5
Overview of the ShARe/CLEF eHealth Evaluation Lab 2014
In: Information Access Evaluation : Multilinguality, Multimodality, and Interaction ; 5th International Conference of the CLEF Initiative, CLEF 2014, Sheffield, UK, September 15-18, 2014. Proceedings / Evangelos Kanoulas . (Hrsg.). - Springer International Publishing, 2014. - (Lecture Notes in Computer Science ; 8685). - S. 172-191. - ISBN 978-3-319-11381-4 (2014)
Abstract: This paper reports on the 2nd ShARe/CLEFeHealth evaluation lab which continues our evaluation resource building activities for the medical domain. In this lab we focus on patients’ information needs as opposed to the more common campaign focus of the specialised information needs of physicians and other healthcare workers. The usage scenario of the lab is to ease patients and next-of-kins’ ease in understanding eHealth information, in particular clinical reports. The 1st ShARe/CLEFeHealth evaluation lab was held in 2013. This lab consisted of three tasks. Task 1 focused on named entity recognition and normalization of disorders; Task 2 on normalization of acronyms/abbreviations; and Task 3 on information retrieval to address questions patients may have when reading clinical reports. This year’s lab introduces a new challenge in Task 1 on visual-interactive search and exploration of eHealth data. Its aim is to help patients (or their next-of-kin) in readability issues related to their hospital discharge documents and related information search on the Internet. Task 2 then continues the information extraction work of the 2013 lab, specifically focusing on disorder attribute identification and normalization from clinical text. Finally, this year’s Task 3 further extends the 2013 information retrieval task, by cleaning the 2013 document collection and introducing a new query generation method and multilingual queries. De-identified clinical reports used by the three tasks were from US intensive care and originated from the MIMIC II database. Other text documents for Tasks 1 and 3 were from the Internet and originated from the Khresmoi project. Task 2 annotations originated from the ShARe annotations. For Tasks 1 and 3, new annotations, queries, and relevance assessments were created. 50, 79, and 91 people registered their interest in Tasks 1, 2, and 3, respectively. 24 unique teams participated with 1, 10, and 14 teams in Tasks 1, 2 and 3, respectively. The teams were from Africa, Asia, Canada, Europe, and North America. The Task 1 submission, reviewed by 5 expert peers, related to the task evaluation category of Effective use of interaction and targeted the needs of both expert and novice users. The best system had an Accuracy of 0.868 in Task 2a, an F1-score of 0.576 in Task 2b, and Precision at 10 (P@10) of 0.756 in Task 3. The results demonstrate the substantial community interest and capabilities of these systems in making clinical reports easier to understand for patients. The organisers have made data and tools available for future research and development.
Keyword: ddc:004; Evaluation; Information Extraction; Information Retrieval; Information Visualisation; Medical Informatics; Test-set Generation; Text Classification; Text Segmentation
URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-0-267233
https://doi.org/10.1007/978-3-319-11382-1_17
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6
Improving performance of natural language processing part-of-speech tagging on clinical narratives through domain adaptation
Ferraro, Jeffrey P; Daumé, Hal; DuVall, Scott L. - : BMJ Publishing Group Ltd, 2013
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7
Identifying Synonymy between SNOMED Clinical Terms of Varying Length Using Distributional Analysis of Electronic Health Records
Henriksson, Aron; Conway, Mike; Duneld, Martin. - : American Medical Informatics Association, 2013
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8
Extending the NegEx Lexicon for Multiple Languages
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9
A system for coreference resolution for the clinical narrative
Zheng, Jiaping; Chapman, Wendy W; Miller, Timothy A. - : BMJ Publishing Group Ltd, 2012
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10
Anaphoric relations in the clinical narrative: corpus creation
Savova, Guergana K; Chapman, Wendy W; Zheng, Jiaping. - : BMJ Publishing Group Ltd, 2011
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11
Building an Automated SOAP Classifier for Emergency Department Reports
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12
Coreference resolution: A review of general methodologies and applications in the clinical domain
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13
Analysis of False Positive Errors of an Acute Respiratory Infection Text Classifier due to Contextual Features
South, Brett R.; Shen, Shuying; Chapman, Wendy W.. - : American Medical Informatics Association, 2010
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14
Context: An Algorithm for Determining Negation, Experiencer, and Temporal Status from Clinical Reports
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15
Inductive creation of an annotation schema for manually indexing clinical conditions from emergency department reports
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