Abstract
Weaning patients efficiently off mechanical ventilation continues to be a challenge for clinical professionals. Medical professionals usually make a decision to wean based mostly on their own experience. In this study, we present a weaning success rate prediction system (WSRPS); it is a computer-aided system developed from MatLab interfaces using Artificial Neural Network (ANN) algorithms. The goal of this system is to help doctors objectively and effectively predict whether weaning is appropriate for patients based on the patients’ clinical data. The system can also output Microsoft EXCEL (XLS) files (i.e. a database including the basic data of patients and doctors) to medical officers. To our knowledge, this is the first design approach of its kind to be used in the study of weaning success rate prediction.
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Chen, A.H., Chen, G.T. (2009). WSRPS: A Weaning Success Rate Prediction System Based on Artificial Neural Network Algorithms. In: Koutsojannis, C., Sirmakessis, S. (eds) Tools and Applications with Artificial Intelligence. Studies in Computational Intelligence, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88069-1_8
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DOI: https://doi.org/10.1007/978-3-540-88069-1_8
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