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Items: 1 to 20 of 113

1.

Natural language processing framework to assess clinical conditions.

Ware H, Mullett CJ, Jagannathan V.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):585-9. doi: 10.1197/jamia.M3091. Epub 2009 Apr 23.

2.

Description of a rule-based system for the i2b2 challenge in natural language processing for clinical data.

Childs LC, Enelow R, Simonsen L, Heintzelman NH, Kowalski KM, Taylor RJ.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):571-5. doi: 10.1197/jamia.M3083. Epub 2009 Apr 23.

3.

A system for classifying disease comorbidity status from medical discharge summaries using automated hotspot and negated concept detection.

Ambert KH, Cohen AM.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):590-5. doi: 10.1197/jamia.M3095. Epub 2009 Apr 23.

4.

Semi-automated construction of decision rules to predict morbidities from clinical texts.

Farkas R, Szarvas G, Hegedus I, Almási A, Vincze V, Ormándi R, Busa-Fekete R.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):601-5. doi: 10.1197/jamia.M3097. Epub 2009 Apr 23.

5.
6.

A rule-based approach for identifying obesity and its comorbidities in medical discharge summaries.

Mishra NK, Cummo DM, Arnzen JJ, Bonander J.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):576-9. doi: 10.1197/jamia.M3086. Epub 2009 Apr 23.

7.

Applying natural language processing toolkits to electronic health records - an experience report.

Barrett N, Weber-Jahnke JH.

Stud Health Technol Inform. 2009;143:441-6.

PMID:
19380974
8.

A text mining approach to the prediction of disease status from clinical discharge summaries.

Yang H, Spasic I, Keane JA, Nenadic G.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):596-600. doi: 10.1197/jamia.M3096. Epub 2009 Apr 23.

9.

Extracting medication information from French clinical texts.

Deléger L, Grouin C, Zweigenbaum P.

Stud Health Technol Inform. 2010;160(Pt 2):949-53.

PMID:
20841824
10.

Discerning tumor status from unstructured MRI reports--completeness of information in existing reports and utility of automated natural language processing.

Cheng LT, Zheng J, Savova GK, Erickson BJ.

J Digit Imaging. 2010 Apr;23(2):119-32. doi: 10.1007/s10278-009-9215-7. Epub 2009 May 30. Review.

11.

Recognizing obesity and comorbidities in sparse data.

Uzuner O.

J Am Med Inform Assoc. 2009 Jul-Aug;16(4):561-70. doi: 10.1197/jamia.M3115. Epub 2009 Apr 23.

12.

Automatic retrieval of bone fracture knowledge using natural language processing.

Do BH, Wu AS, Maley J, Biswal S.

J Digit Imaging. 2013 Aug;26(4):709-13. doi: 10.1007/s10278-012-9531-1.

13.

Integrating existing natural language processing tools for medication extraction from discharge summaries.

Doan S, Bastarache L, Klimkowski S, Denny JC, Xu H.

J Am Med Inform Assoc. 2010 Sep-Oct;17(5):528-31. doi: 10.1136/jamia.2010.003855.

14.

Disseminating natural language processed clinical narratives.

Chen ES, Hripcsak G, Friedman C.

AMIA Annu Symp Proc. 2006:126-30.

15.

Representing information in patient reports using natural language processing and the extensible markup language.

Friedman C, Hripcsak G, Shagina L, Liu H.

J Am Med Inform Assoc. 1999 Jan-Feb;6(1):76-87.

16.

Discovery of association rules in medical data.

Doddi S, Marathe A, Ravi SS, Torney DC.

Med Inform Internet Med. 2001 Jan-Mar;26(1):25-33.

PMID:
11583406
17.

Extracting phenotypic information from the literature via natural language processing.

Chen L, Friedman C.

Stud Health Technol Inform. 2004;107(Pt 2):758-62.

PMID:
15360914
18.

Medical i2b2 NLP smoking challenge: the A-Life system architecture and methodology.

Heinze DT, Morsch ML, Potter BC, Sheffer RE Jr.

J Am Med Inform Assoc. 2008 Jan-Feb;15(1):40-3. Epub 2007 Oct 18.

19.

Linguistic approach for identification of medication names and related information in clinical narratives.

Hamon T, Grabar N.

J Am Med Inform Assoc. 2010 Sep-Oct;17(5):549-54. doi: 10.1136/jamia.2010.004036.

20.

A clinical use case to evaluate the i2b2 Hive: predicting asthma exacerbations.

Meystre SM, Deshmukh VG, Mitchell J.

AMIA Annu Symp Proc. 2009 Nov 14;2009:442-6.

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