Authors:
Noriaki Ikeda
;
Kai Ishida
;
Harukazu Tsuruta
and
Akihiro Takeuchi
Affiliation:
Kitasato University, Japan
Keyword(s):
Multiple tests, Diagnostic performance, Correlation between tests, Logistic model, Neural nets.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computer-Supported Education
;
Domain Applications and Case Studies
;
Fuzzy Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Industrial, Financial and Medical Applications
;
Methodologies and Methods
;
Neural Based Data Mining and Complex Information Processing
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
To examine the improvement of diagnostic performance by combining multiple tests, an algorithm was developed for generation of simulated data with arbitrary sensitivity, specificity and inter-test correlations. The effects of the number of tests and inter-test correlations on the diagnostic performance were studied using a logistic model and neural network (NN) models. The diagnostic performance measured by the concordance index, c, increased as the number of tests increased. For the same number of tests, the diagnostic performance was lowered by positive correlation and was elevated by negative correlation. Improvement of the performance was not obtained by increasing the number of NN layers.