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Items: 1 to 20 of 100

1.

Discovering body site and severity modifiers in clinical texts.

Dligach D, Bethard S, Becker L, Miller T, Savova GK.

J Am Med Inform Assoc. 2014 May-Jun;21(3):448-54. doi: 10.1136/amiajnl-2013-001766. Epub 2013 Oct 3.

2.

A flexible framework for deriving assertions from electronic medical records.

Roberts K, Harabagiu SM.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):568-73. doi: 10.1136/amiajnl-2011-000152. Epub 2011 Jul 1.

3.

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications.

Savova GK, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, Chute CG.

J Am Med Inform Assoc. 2010 Sep-Oct;17(5):507-13. doi: 10.1136/jamia.2009.001560.

4.

Causality patterns and machine learning for the extraction of problem-action relations in discharge summaries.

Seol JW, Yi W, Choi J, Lee KS.

Int J Med Inform. 2017 Feb;98:1-12. doi: 10.1016/j.ijmedinf.2016.10.021. Epub 2016 Nov 9.

PMID:
28034407
5.

A flexible framework for recognizing events, temporal expressions, and temporal relations in clinical text.

Roberts K, Rink B, Harabagiu SM.

J Am Med Inform Assoc. 2013 Sep-Oct;20(5):867-75. doi: 10.1136/amiajnl-2013-001619. Epub 2013 May 18.

6.

Automatic extraction of relations between medical concepts in clinical texts.

Rink B, Harabagiu S, Roberts K.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):594-600. doi: 10.1136/amiajnl-2011-000153.

7.

Information extraction from multi-institutional radiology reports.

Hassanpour S, Langlotz CP.

Artif Intell Med. 2016 Jan;66:29-39. doi: 10.1016/j.artmed.2015.09.007. Epub 2015 Oct 3.

8.

Recognizing names in biomedical texts: a machine learning approach.

Zhou G, Zhang J, Su J, Shen D, Tan C.

Bioinformatics. 2004 May 1;20(7):1178-90. Epub 2004 Feb 10.

PMID:
14871877
9.

Hybrid methods for improving information access in clinical documents: concept, assertion, and relation identification.

Minard AL, Ligozat AL, Ben Abacha A, Bernhard D, Cartoni B, Del├ęger L, Grau B, Rosset S, Zweigenbaum P, Grouin C.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):588-93. doi: 10.1136/amiajnl-2011-000154. Epub 2011 May 19.

10.

Mining clinical relationships from patient narratives.

Roberts A, Gaizauskas R, Hepple M, Guo Y.

BMC Bioinformatics. 2008 Nov 19;9 Suppl 11:S3. doi: 10.1186/1471-2105-9-S11-S3.

11.

A system for coreference resolution for the clinical narrative.

Zheng J, Chapman WW, Miller TA, Lin C, Crowley RS, Savova GK.

J Am Med Inform Assoc. 2012 Jul-Aug;19(4):660-7. doi: 10.1136/amiajnl-2011-000599. Epub 2012 Jan 31.

12.

Data-Driven Information Extraction from Chinese Electronic Medical Records.

Xu D, Zhang M, Zhao T, Ge C, Gao W, Wei J, Zhu KQ.

PLoS One. 2015 Aug 21;10(8):e0136270. doi: 10.1371/journal.pone.0136270. eCollection 2015.

13.

A Relation Extraction Framework for Biomedical Text Using Hybrid Feature Set.

Muzaffar AW, Azam F, Qamar U.

Comput Math Methods Med. 2015;2015:910423. doi: 10.1155/2015/910423. Epub 2015 Aug 10.

14.

The Yale cTAKES extensions for document classification: architecture and application.

Garla V, Lo Re V 3rd, Dorey-Stein Z, Kidwai F, Scotch M, Womack J, Justice A, Brandt C.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):614-20. doi: 10.1136/amiajnl-2011-000093. Epub 2011 May 27.

15.

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

Jiang M, Chen Y, Liu M, Rosenbloom ST, Mani S, Denny JC, Xu H.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):601-6. doi: 10.1136/amiajnl-2011-000163. Epub 2011 Apr 20.

16.

Generation of silver standard concept annotations from biomedical texts with special relevance to phenotypes.

Oellrich A, Collier N, Smedley D, Groza T.

PLoS One. 2015 Jan 21;10(1):e0116040. doi: 10.1371/journal.pone.0116040. eCollection 2015.

17.

Multilayered temporal modeling for the clinical domain.

Lin C, Dligach D, Miller TA, Bethard S, Savova GK.

J Am Med Inform Assoc. 2016 Mar;23(2):387-95. doi: 10.1093/jamia/ocv113. Epub 2015 Oct 31.

18.

BIOSMILE: a semantic role labeling system for biomedical verbs using a maximum-entropy model with automatically generated template features.

Tsai RT, Chou WC, Su YS, Lin YC, Sung CL, Dai HJ, Yeh IT, Ku W, Sung TY, Hsu WL.

BMC Bioinformatics. 2007 Sep 1;8:325.

19.

Automatic identification and classification of noun argument structures in biomedical literature.

Ozyurt IB.

IEEE/ACM Trans Comput Biol Bioinform. 2012 Nov-Dec;9(6):1639-48.

PMID:
22868678
20.

Extracting biomedical events from pairs of text entities.

Liu X, Bordes A, Grandvalet Y.

BMC Bioinformatics. 2015;16 Suppl 10:S8. doi: 10.1186/1471-2105-16-S10-S8. Epub 2015 Jul 13.

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