Predicting Chronic Diseases with Health IT: a Survey on Popular Techniques
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2019 by IJETT Journal | ||
| Volume-67 Issue-6 |
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| Year of Publication : 2019 | ||
| Authors : Tongbin Zhang, Li Cai, Chuandi Pan |
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| DOI : 10.14445/22315381/IJETT-V67I6P204 |
Citation
MLA Style: Tongbin Zhang, Li Cai, Chuandi Pan"Predicting Chronic Diseases with Health IT: a Survey on Popular Techniques" International Journal of Engineering Trends and Technology 67.6 (2019): 18-24.
APA Style:Tongbin Zhang, Li Cai, Chuandi Pan (2019). Predicting Chronic Diseases with Health IT: a Survey on Popular Techniques International Journal of Engineering Trends and Technology, 67(6), 18-24.
Abstract
In this paper, we study and compare popular predictive techniques to predict the chronic diseases with the support of health information technology. Interestingly, we show that there is no technique guaranteeing the good predictive outcomes for all diseases. In many cases, the well-known state-of-the-art techniques, such as support vector machine, was significantly outperformed by simpler classical techniques. We also show that using feature selection would improve the predictive performance. However, choosing the right predictive technique is still the crucial factor. Therefore, in health information technology industrial practice, the predictive healthcare system should change from only relying on only one technique to integrating multiple techniques in case-study basis.
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Keywords
Chronic disease prediction, Health IT, Random Forest