Name
Abstract | ||
|---|---|---|
Environments such as healthcare systems rely on wireless sensor networks as one of the trends being established in today's industry. Being one of the most researched topics today, ubiquitous healthcare is mostly concerned with providing fast and efficient service. This paper proposes the Health Monitor Agent (HMA) to monitor patients' conditions, provide early detection of serious cases, and take appropriate action in case of emergency. We present this agent to the Ubiquitous and Intelligent Framework. The proposed agent recognizes medical conditions based on symptom patterns from the biosensors in the ubiquitous healthcare environment. The HMA classifies the symptom patterns into the correct medical condition using the multilayer perceptron (MLP). Our proposed algorithm recorded the highest accuracy rate compared to the ZeroR, Simple Logistic, and J48 algorithms. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-01665-3_38 | KES-AMSTA |
Keywords | Field | DocType |
multilayer perceptron,wireless sensor network,neural network | Data mining,Early detection,Computer security,Computer science,Mobile agent,C4.5 algorithm,Multilayer perceptron,Artificial intelligence,Healthcare system,Artificial neural network,Health care,Wireless sensor network,Machine learning | Conference |
Volume | ISSN | Citations |
5559 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Angelo G. Salvo | 1 | 1 | 0.36 |
| Romeo Mark A. Mateo | 2 | 37 | 7.20 |
| Jaewan Lee | 3 | 62 | 14.66 |
| Malrey Lee | 4 | 197 | 41.30 |