A Rule-based Approach for Identifying Obesity and Its Comorbidities in Medical Discharge Summaries

Journal of the American Medical Informatics Association

Volumn 16, Issue 4, 2009, Pages 576-579

  Mishra, Ninad K ^a   Cummo, David M ^b   Arnzen, James J ^b   Bonander, Jason ^a  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^b NORTHROP GRUMMAN CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMORBIDITY; DISEASE ASSOCIATION; DISEASE CLASSIFICATION; HOSPITAL DISCHARGE; HUMAN; OBESITY;

COMORBIDITY; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; NATURAL LANGUAGE PROCESSING; OBESITY; PATIENT DISCHARGE;

EID: 67649343941     PISSN: 10675027     EISSN: None     Source Type: Journal    
DOI: 10.1197/jamia.M3086     Document Type: Article

References (12)

1. Wilcox A.B., and Hripcsak G. The role of domain knowledge in automating medical text report classification. J Am Med Inform Assoc 10 (2003) 330-338
2. Chapman W.W., Cooper G.F., Hanbury P., et al. Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders. J Am Med Inform Assoc 10 5 (2003) 494-503
3. th Int FLAIRS Conference (2003) 412-416
4. Clark C., Good K., Jezierny L., et al. Identifying smokers with a medical extraction system. J Am Med Inform Assoc 15 (2008) 36-39
5. Fiszman M., Chapman W.W., Aronsky D., Evans R.S., and Haug P.J. Automatic detection of acute bacterial pneumonia from chest x-ray reports. J Am Med Inform Assoc 7 (2000) 593-604
6. Chapman W.W., Christensen L.M., Wagner M.M., et al. Classifying free-text triage chief complaints into syndromic categories with natural language processing. Artif Intell Med 33 1 (2005) 31-40
7. Zeng Q.T., Goryachev S., Weiss S., et al. Extracting principal diagnosis, co-morbidity and smoking status for asthma research: Evaluation of a natural language processing system. BMC Med Inform Decis Mak 6 (2006) 30
8. Dumais S.T., Platt J., Heckerman D., and Sahami M. Inductive learning algorithms and representations for text categorization. Proceedings of the 7th ACM International Conference on Information and Knowledge Management (1998), ACM Press, New York 148-155
9. Uzuner O., Szolovits P., and Kohane I. Second i. 2b2 shared-task and workshop [internet]. i2b2: Informatics for integrating biology and the bedside (2008). https://www.i2b2.org/NLP/ Accessed: Aug 15, 2008
10. Chapman W.W., Bridewell W., Hanbury P., Cooper G.F., and Buchanan B.G. A simple algorithm for identifying negated findings and diseases in discharge summaries. J Biomed Inform 34 (2001) 301-310
11. Uzuner O. Recognizing obesity and co-morbidities in sparse data. J Am Med Inform Assoc 16 (2009) 560-570
12. Chapman W.W., Chu D., and Dowling J.N. ConText: An algorithm for identifying contextual features from clinical text. Proceedings of the 2007 ACL Workshop on Biological, Translational, and Clinical Language Processing (BioNLP); 2007 Jun 29; Prague, Czech Republic (2007), Omnipress, Madison, WI 81-88