The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Analyzing Healthcare Big Data With Prediction for Future Health Condition
Open accessAbstract
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.
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Cites
Big data analytics in healthcare: promise and potential
Raghupathi, W., & Raghupathi, V. (2014) · Health Information Science and Systems · doi:10.1186/2047-2501-2-3 · Cited by 3,034
Disease inference from health-related questions via sparse deep learning
Nie, L., Wang, M., Zhang, L., Yan, S., Zhang, B., & Chua, T.-S. (2015) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2015.2399298 · Cited by 195
Cited by
Bhuiyan, M. N., Rahman, M. M., Billah, M. M., & Saha, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3062630 · Cited by 490
Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach
Fang, S.-H., Tsao, Y., Hsiao, M.-J., Chen, J.-Y., Lai, Y.-H., Lin, F.-C., & Wang, C.-T. (2019) · Journal of Voice · doi:10.1016/j.jvoice.2018.02.003 · Cited by 278
A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health
Sahoo, P., Thakkar, H., & Lee, M.-Y. (2017) · Sensors · doi:10.3390/s17040711 · Cited by 81
Self-citationStudy on IoT for SARS-CoV-2 with healthcare: present and future perspective
Rahman, A., Department of Computer Science and Engineering, N. I. O. T. E. A. R. (., Rahman, M., Kundu, D., Karim, M. R., Band, S. S., Sookhak, M., Department of Computer Science and Engineering, M. B. S. A. T. U., Department of Electrical and Electronic Engineering, N. I. O. T. E. A. R. (., Future Technology Research Center, C. O. F., et al. (2021) · Mathematical Biosciences and Engineering · doi:10.3934/mbe.2021475 · Cited by 22
Passive Health Monitoring Using Large Scale Mobility Data
Zhang, Y., Xu, F., Li, T., Kostakos, V., Hui, P., & Li, Y. (2021) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3448078 · Cited by 10
Metadata
- Authors
- Sahoo, P. K., Mohapatra, S. K., & Wu, S.-L.
- Venue
- IEEE Access
- Published
- 2016
- Volume
- 4
- Pages
- 9786-9799
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2571067114
- Cited by
- 160
- References
- 2
- FWCI
- 20.62
- Type
- journal article
- Language
- en
- Open access
- gold
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