Genetic programming outperformed multivariable logistic regression in diagnosing pulmonary embolism
نویسندگان
چکیده
منابع مشابه
Genetic programming outperformed multivariable logistic regression in diagnosing pulmonary embolism.
OBJECTIVE Genetic programming is a search method that can be used to solve complex associations between large numbers of variables. It has been used, for example, for myoelectrical signal recognition, but its value for medical prediction as in diagnostic and prognostic settings, has not been documented. STUDY DESIGN AND SETTING We compared genetic programming and the commonly used logistic re...
متن کاملDiagnosing pulmonary embolism
No single non invasive test has sufficient diagnostic accuracy to be used alone for diagnosing or ruling out pulmonary embolism. Therefore, modern diagnostic strategies for pulmonary embolism rely on combinations of non invasive tests such as plasma D-dimer measurement, lower limb venous compression ultrasonography, ventilation-perfusion lung scan and/or spiral CT, the results of which should b...
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In designing non-linear classifiers, there are important trade-offs to be made between predictive accuracy and model comprehensibility or complexity. We introduce the use of Genetic Programming to generate logistic polynomial models, a relatively comprehensible non-linear parametric model; describe an efficient twostage algorithm consisting of GP structure design and Quasi-Newton coefficient se...
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ژورنال
عنوان ژورنال: Journal of Clinical Epidemiology
سال: 2004
ISSN: 0895-4356
DOI: 10.1016/j.jclinepi.2003.10.011