Name
Abstract | ||
|---|---|---|
•Medical data accuracy challenges for mobile healthcare applications are studied.•An anomaly detection and isolation approach is proposed.•Multivariate anomaly detection is preceded by principal component analysis based dimension reduction step.•Univariate anomaly isolation is provided to distinguish between inaccurate data and patient health degradation.•The proposed approach is evaluated on real medical dataset and compared with existing solutions. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compind.2018.01.020 | Computers in Industry |
Keywords | Field | DocType |
Accuracy,Mobile healthcare application,Anomaly detection,Anomaly isolation,Dimension reduction,Principal Component Analysis,Robustness | Health care,Data accuracy,Anomaly detection,Data mining,Dimensionality reduction,Data detection,Multivariate statistics,Control engineering,Constant false alarm rate,Engineering,Principal component analysis | Journal |
Volume | ISSN | Citations |
97 | 0166-3615 | 2 |
PageRank | References | Authors |
0.37 | 20 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lamia Ben Amor | 1 | 6 | 3.15 |
| Imene Lahyani | 2 | 23 | 7.05 |
| Mohamed Jmaiel | 3 | 668 | 110.41 |