کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4944808 | 1438009 | 2017 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Reality mining: A prediction algorithm for disease dynamics based on mobile big data
ترجمه فارسی عنوان
معدن واقعیت: یک الگوریتم پیش بینی برای پویایی بیماری بر اساس داده های بزرگ تلفن همراه
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کلمات کلیدی
معدن واقعیت دینامیک بیماری، الگوریتم پیش بینی، داده های بزرگ تلفن همراه
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Predicting disease dynamics during an epidemic is an important aspect of e-Health applications. In such prediction, Realistic Contact Networks (RCNs) have been widely used to characterize disease dynamics. The structure of such networks is dynamically changed during an epidemic. Capturing such kind of dynamic structure is the basis of prediction. With the popularity of mobile devices, it is possible to capture the dynamic change of the network structure. On this basis, in this study, we evaluate the impact of the network structure on disease dynamics, by analyzing massive spatiotemporal data collected by mobile devices. These devices are carried by the volunteers of Ebola outbreak areas. Based on the results of this evaluation, a model is designed to recognize the dynamic structure of RCNs. On the basis of this model, we propose a prediction algorithm for disease dynamics. By extensive experiments, we show that our algorithm improves the accuracy of the disease prediction.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 379, 10 February 2017, Pages 82-93
Journal: Information Sciences - Volume 379, 10 February 2017, Pages 82-93
نویسندگان
Yuanfang Chen, Noel Crespi, Antonio M. Ortiz, Lei Shu,