| Autor: |
Prasan Kumar Sahoo, Suvendu Kumar Mohapatra, Shih-Lin Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 4, Pp 9786-9799 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2016.2647619 |
| Popis: |
In healthcare management, a large volume of multi-structured patient data is generated from the clinical reports, doctor's notes, and wearable body sensors. The analysis of healthcare parameters and the prediction of the subsequent future health conditions are still in the informative stage. A cloud-enabled big data analytic platform is the best way to analyze the structured and unstructured data generated from healthcare management systems. In this paper, a probabilistic data collection mechanism is designed and the correlation analysis of those collected data is performed. Finally, a stochastic prediction model is designed to foresee the future health condition of the most correlated patients based on their current health status. Performance evaluation of the proposed protocols is realized through extensive simulations in the cloud environment, which gives about 98% accuracy of prediction, and maintains 90% of CPU and bandwidth utilization to reduce the analysis time. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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