Big Data in Patient Health Monitoring System
2020
- 22Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage22
- Abstract Views22
Artifact Description
Health monitoring improves better quality of care, helps prevent complications and enables patients to be proactive about their health. Big Data as new technology, can improve the monitoring of patients health care. Towards this, the health monitoring system involves collecting, processing and analyzing large amounts of data coming from various sources. These data are important for diagnose and treatment of patient. In this paper a patient monitoring system using MongoDB as NoSQL data store have proposed. This method includes collecting and analyzing patient’s health data to control and monitor continuously the parameters of health conditions.
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