Open Science Research Excellence
%0 Journal Article
%A Guilherme Ribeiro and  Alexandre Oliveira and  Antonio Ferreira and  Shyam Visweswaran and  Gregory Cooper
%D 2016 
%J  International Journal of Computer and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 109, 2016
%T Patient-Specific Modeling Algorithm for Medical Data Based on AUC
%V 109
%X Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
%P 105 - 110