Optimization of arterial age prediction models based in pulse wave
| Autor: | Lucía Isabel Passoni, Gustavo J. Meschino, A. L. Dai Pra, Anibal R. Introzzi, Adriana G. Scandurra, Fernando M. Clara |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
History
Engineering Artificial neural network business.industry Age prediction Chronological age Machine learning computer.software_genre Computer Science Applications Education Fuzzy inference system Principal component analysis Coherence (signal processing) Pulse wave Artificial intelligence business computer Algorithm Arterial ageing |
| Zdroj: | Journal of Physics: Conference Series. 90:012080 |
| ISSN: | 1742-6596 |
| DOI: | 10.1088/1742-6596/90/1/012080 |
| Popis: | We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|