Document Detail


Methodology for the differential diagnosis of a complex data set. A case study using data from routine CT scan examinations.
MedLine Citation:
PMID:  6633185     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Data from routine CT scan examinations are employed to illustrate the use of the polychotomous logistic regression model as a statistical diagnostic tool. The assumptions of the model, the interpretation of its parameters, and its capabilities are described in detail. In carrying out the analysis on the CT data, a large, relatively sparse data set, many technical difficulties were encountered. Modifications to the methodology that were necessary to permit its implementation are described, and it is demonstrated that an unbiased analysis of T + 1 diagnostic categories can be implemented by separately performing T individual simple logistic analyses. The limitations of the methodology are discussed. It is hoped that this paper may serve as a basis for the practical implementation of the polychotomous logistic model in similar diagnostic settings.
Authors:
A Wijesinha; C B Begg; H H Funkenstein; B J McNeil
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Medical decision making : an international journal of the Society for Medical Decision Making     Volume:  3     ISSN:  0272-989X     ISO Abbreviation:  Med Decis Making     Publication Date:  1983  
Date Detail:
Created Date:  1983-12-20     Completed Date:  1983-12-20     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  8109073     Medline TA:  Med Decis Making     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  133-54     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Brain Diseases / radiography
Diagnosis, Differential*
Humans
Mathematics
Methods
Middle Aged
Models, Theoretical
Probability
Tomography, X-Ray Computed
Grant Support
ID/Acronym/Agency:
CA-28847/CA/NCI NIH HHS; CA-31247/CA/NCI NIH HHS; NLM 04301-02/LM/NLM NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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