Abstract
With the rapid growth of machine learning algorithms, the artificial intelligence classification technology serves as a useful and an important reference for physicians or non-specialists to make a diagnosis. In this paper, we designed a health assistant that aims at enhancing the quality and the performance of healthcare services. We intend to develop communication technologies between cloud platform and mobile applications to resolve the data-storage shortage of portable devices. Contribution of our work includes the use of effective and efficient machine learning algorithms (i.e. Bayesian Network, C5.0, Neural Network and Neural-C5.0) which have been compared and applied to diagnosis a heart disease. Our study conducted four experiments and constructed a model on the cloud. And this article summaries the implementation details and presents the results of our study.
The authors contributed equally to this work.
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Huang, G., Chen, L., Feng, Z. (2016). Health Assistant Based on Cloud Platform . In: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_43
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DOI: https://doi.org/10.1007/978-3-319-39601-9_43
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