Document Detail

Categorical similarity comparison of ciren and nass.
MedLine Citation:
PMID:  19141933     Owner:  NLM     Status:  In-Data-Review    
In vehicle crash and injury databases, it is beneficial to have a similarity metric between databases so that cases can be compared and used in analyses. The Mahalanobis metric was used to quantitatively score the similarity between certain database entries in Crash Injury Research and Engineering Network (CIREN) cases and those same entries in the National Automotive Sampling System (NASS) population. One difficulty with this is that many fields within CIREN and NASS are non-ordinal in nature, requiring additional preprocessing prior to analysis. This study presents an implementation of the Mahalanobis metric for converting many non-ordinal discrete fields to ordinal fields via a preprocessing function specific to each field. The cases were split into categories and a subset of NASS cases was used as the population. The search region was defined to be a common crash scenario. Seven important fields from the analysis were utilized. The results of this specific analysis showed that the three most similar cases in CIREN were within the search region defined in NASS. Therefore, the Mahalanobis metric has been shown to be a viable similarity scoring system for non-ordinal NASS database entries.
Mao M Yu; Kerry A Danelson; Joel D Stitzel
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biomedical sciences instrumentation     Volume:  44     ISSN:  0067-8856     ISO Abbreviation:  Biomed Sci Instrum     Publication Date:  2008  
Date Detail:
Created Date:  2009-01-14     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0140524     Medline TA:  Biomed Sci Instrum     Country:  United States    
Other Details:
Languages:  eng     Pagination:  304-9     Citation Subset:  IM    
Wake Forest University School of Medicine, Virginia Tech - Wake Forest University Center for Injury Biomechanics, USA.
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