A major public health problem is the chronically respiratory ill patients. To create a more preventive and anticipatory system for these patients we can use artificial intelligence techniques. Thiswork tackle the problem of developing amodel for automatic classification of patients with risk of having a respiratory crisis on the biggest paediatric Public Hospital in Santiago, Chile. We present a benchmark of different approaches to create a model. The models were developed with history of biomedical signals for 45 patients from 0 months to 15 years old. We are able to identify to approaches which have a remarkable performance.
CITATION STYLE
Ríos, S. A., Tenorio, F. G., & Jimenez-Molina, A. (2016). A benchmark on artificial intelligence techniques for automatic chronic respiratory diseases risk classification. In Smart Innovation, Systems and Technologies (Vol. 45, pp. 471–481). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-23024-5_43
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