This paper presents an ontology-based intelligent agent for respiretory waveform classification to help the medical staff with the judging the respiratory waveform from the ventilator. We present the manual construction tool (MCT), the respiratory waveform ontology (RWO), and the intelligent classification agent (ICA) to implement the classification of the respiratory waveform. The MCT allows the medical experts to construct and store fuzzy numbers of respiratory waveforms to the RWO. When the ICA receives an input respiratory waveform (IRW), it will retrieve the fuzzy numbers from the RWO to carry out the classification task. Next, the ICA will send the classified results to the medical experts to make a confirmation and store the classified results to the classified waveform repository (CWR). The experimental results show that our approach can classify the respiratory waveform effectively and efficiently. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Lee, C. S., & Wang, M. H. (2006). An ontology-based intelligent agent for respiratory waveform classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4031 LNAI, pp. 1240–1248). Springer Verlag. https://doi.org/10.1007/11779568_131
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