Abstract
Tuberculosis is an infectious disease widely present in developing countries, which is largely motivated by the difficulty of a rapid and efficient diagnosis. In order to reduce the number of patients suspected of having TB unnecessarily isolated in hospitals, thus optimize the use of health resources, we propose a systematic procedure for developing a decision support system based on specialized MLP network committee. The system based on 3 MLP models, which response to input data clusters inferred by the k-means technique, exhibits a better classification performance than a single network in terms of the number of false positives, achieving a sensitivity of 83.3% and specificity of 94.3%. © 2013 IEEE.
Author supplied keywords
Cite
CITATION STYLE
Dos Santos Alves, E., Filho, J. B. O. S., Galliez, R. M., & Kritski, A. (2013). Specialized MLP classifiers to support the isolation of patients suspected of pulmonary tuberculosis. In Proceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013 (pp. 40–45). IEEE Computer Society. https://doi.org/10.1109/BRICS-CCI-CBIC.2013.18
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.