Literature DB >> 12784968

GOLDmineR: improving models for classifying patients with chest pain.

Larry Bernstein1, Keith Bradley, Stuart Zarich.   

Abstract

The laboratory is dealing with reporting tests as information needed to make clinical decisions. The traditional statistical quality control measures which assigns reference ranges based on 95 percent confidence intervals is insufficient for diagnostic tests that assign risk. We construct a basis for risk assignment by a method that builds on the 2 x 2 contingency table used to calculate the C2 goodness-of-fit and Bayesian estimates. The widely used logistic regression is a subset of the regression method, as it only considers dichotomous outcome choices. We use examples of multivalued predictor(s) and a multivalued as well as dichotomous outcome. Outcomes analyses are quite easy using the ordinal logit regression model.

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Year:  2002        PMID: 12784968      PMCID: PMC2588788     

Source DB:  PubMed          Journal:  Yale J Biol Med        ISSN: 0044-0086


  3 in total

1.  Enhancing laboratory detection of disease. Part 2: Amplifying information and requisite variety.

Authors:  E W Rypka; D A Madar
Journal:  Am Clin Lab       Date:  1997-03

2.  A computer-derived protocol to aid in the diagnosis of emergency room patients with acute chest pain.

Authors:  L Goldman; M Weinberg; M Weisberg; R Olshen; E F Cook; R K Sargent; G A Lamas; C Dennis; C Wilson; L Deckelbaum; H Fineberg; R Stiratelli
Journal:  N Engl J Med       Date:  1982-09-02       Impact factor: 91.245

3.  Information induction for predicting acute myocardial infarction.

Authors:  R A Rudolph; L H Bernstein; J Babb
Journal:  Clin Chem       Date:  1988-10       Impact factor: 8.327

  3 in total

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