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Selection of variables using ‘independence bayes’ in computer‐aided diagnosis of upper gastrointestinal bleeding
Author(s) -
Ohmann C.,
Künneke M.,
Zaczyk R.,
Thon K.,
Lorenz W.
Publication year - 1986
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780050515
Subject(s) - independence (probability theory) , bayes' theorem , selection (genetic algorithm) , statistics , conditional independence , monotonic function , feature selection , stability (learning theory) , computer science , mathematics , artificial intelligence , bayesian probability , machine learning , mathematical analysis
In this paper two problems of computer‐aided diagnosis with ‘independence Bayes’ were investigated: selection of variables and monotonicity in performance as the number of measurements is increased. Using prospective data from patients with upper gastrointestinal bleeding, the stepwise forward selection approach maximizing the apparent diagnostic accuracy was analysed with respect to different kinds of bias in estimation of the true diagnostic accuracy and to the stability of the number and type of variables selected. The results of this study suggest first that the selection of variables should be evaluated against the estimated true diagnostic accuracy obtained using all variables, and secondly that the results of a single selected sequence may be severely biased.