Using Natural Language Processing and the Electronic Health Record for Appendicitis Risk Stratification

This study evaluated an automated approach for appendicitis risk stratification of pediatric Emergency Department patients using Conditional Random Fields, rules and Support Vector Machines. The results show that the approach is very promising for appendicitis risk stratification.

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Bibliographic Details
Main Authors: Deleger, L., Brodzinski, H., Haijun Zhai, Qi Li, Lingren, T., Kirkendall, E., Alessandrini, E., Solti, I.
Format: Conference Proceeding
Language:English
Subjects:
Hospitals
Medical diagnostic imaging
Natural language processing
Pain
Pediatrics
Support vector machines
Online Access:Request full text
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Description
Summary:This study evaluated an automated approach for appendicitis risk stratification of pediatric Emergency Department patients using Conditional Random Fields, rules and Support Vector Machines. The results show that the approach is very promising for appendicitis risk stratification.
DOI:10.1109/HISB.2012.15