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Items: 1 to 20 of 88

1.

Automated extraction of the Barthel Index from clinical texts.

Giang P, Williams A, Argyros L.

AMIA Annu Symp Proc. 2013 Nov 16;2013:486-95. eCollection 2013.

2.

Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies.

Cohen R, Elhadad M, Elhadad N.

BMC Bioinformatics. 2013 Jan 16;14:10. doi: 10.1186/1471-2105-14-10.

3.

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.

4.

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

Yu S, Liao KP, Shaw SY, Gainer VS, Churchill SE, Szolovits P, Murphy SN, Kohane IS, Cai T.

J Am Med Inform Assoc. 2015 Sep;22(5):993-1000. doi: 10.1093/jamia/ocv034. Epub 2015 Apr 29.

5.

Using natural language processing to identify problem usage of prescription opioids.

Carrell DS, Cronkite D, Palmer RE, Saunders K, Gross DE, Masters ET, Hylan TR, Von Korff M.

Int J Med Inform. 2015 Dec;84(12):1057-64. doi: 10.1016/j.ijmedinf.2015.09.002. Epub 2015 Sep 25.

PMID:
26456569
6.

Development of text mining based classification of written communication within a telemedical collaborative network.

Gruber K, Modre-Osprian R, Kreiner K, Kastner P, Schreier G.

Stud Health Technol Inform. 2015;212:35-42.

PMID:
26063255
7.

Mining the electronic health record for disease knowledge.

Chen ES, Sarkar IN.

Methods Mol Biol. 2014;1159:269-86. doi: 10.1007/978-1-4939-0709-0_15. Review.

PMID:
24788272
8.

A knowledge discovery and reuse pipeline for information extraction in clinical notes.

Patrick JD, Nguyen DH, Wang Y, Li M.

J Am Med Inform Assoc. 2011 Sep-Oct;18(5):574-9. doi: 10.1136/amiajnl-2011-000302. Epub 2011 Jul 7.

9.

Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases.

Xu H, Fu Z, Shah A, Chen Y, Peterson NB, Chen Q, Mani S, Levy MA, Dai Q, Denny JC.

AMIA Annu Symp Proc. 2011;2011:1564-72. Epub 2011 Oct 22.

10.

A novel feature selection strategy for enhanced biomedical event extraction using the Turku system.

Xia J, Fang AC, Zhang X.

Biomed Res Int. 2014;2014:205239. doi: 10.1155/2014/205239. Epub 2014 Apr 6.

11.

Extraction of Vital Signs from Clinical Notes.

Patterson OV, Jones M, Yao Y, Viernes B, Alba PR, Iwashyna TJ, DuVall SL.

Stud Health Technol Inform. 2015;216:1035.

PMID:
26262334
12.

MedEx: a medication information extraction system for clinical narratives.

Xu H, Stenner SP, Doan S, Johnson KB, Waitman LR, Denny JC.

J Am Med Inform Assoc. 2010 Jan-Feb;17(1):19-24. doi: 10.1197/jamia.M3378.

13.

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.

14.

Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text.

Heintzelman NH, Taylor RJ, Simonsen L, Lustig R, Anderko D, Haythornthwaite JA, Childs LC, Bova GS.

J Am Med Inform Assoc. 2013 Sep-Oct;20(5):898-905. doi: 10.1136/amiajnl-2012-001076. Epub 2012 Nov 9.

15.

Detecting concept relations in clinical text: insights from a state-of-the-art model.

Zhu X, Cherry C, Kiritchenko S, Martin J, de Bruijn B.

J Biomed Inform. 2013 Apr;46(2):275-85. doi: 10.1016/j.jbi.2012.11.006. Epub 2013 Feb 4.

16.

Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records.

Byrd RJ, Steinhubl SR, Sun J, Ebadollahi S, Stewart WF.

Int J Med Inform. 2014 Dec;83(12):983-92. doi: 10.1016/j.ijmedinf.2012.12.005. Epub 2013 Jan 11.

17.

A semantic model for multimodal data mining in healthcare information systems.

Iakovidis D, Smailis C.

Stud Health Technol Inform. 2012;180:574-8.

PMID:
22874256
18.

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.

19.

Textual inference for eligibility criteria resolution in clinical trials.

Shivade C, Hebert C, Lopetegui M, de Marneffe MC, Fosler-Lussier E, Lai AM.

J Biomed Inform. 2015 Dec;58 Suppl:S211-8. doi: 10.1016/j.jbi.2015.09.008. Epub 2015 Sep 14.

20.

Automated extraction of clinical traits of multiple sclerosis in electronic medical records.

Davis MF, Sriram S, Bush WS, Denny JC, Haines JL.

J Am Med Inform Assoc. 2013 Dec;20(e2):e334-40. doi: 10.1136/amiajnl-2013-001999. Epub 2013 Oct 22.

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