Name
Abstract | ||
|---|---|---|
Data Mining (DM) techniques such as classification, clustering, association, regression etc. provide a promising way to help improving the quality, efficiency and lowing the cost of developing the healthcare systems. Especially with the rapid development of the cloud platform services, like SaaS, it does not only reduce the cost (time and expenditure) but also breaks the boundaries of the data transaction among different systems and users. In this work, we briefly described a healthcare system based on SaaS services for disease detection and prediction by using DM techniques so as to provide better service for both patients and health care givers. Promisingly, our work will provide a guideline for the next stage of research. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICMLC.2016.7873001 | 2016 International Conference on Machine Learning and Cybernetics (ICMLC) |
Keywords | Field | DocType |
SaaS,Data Mining,Healthcare System | Data science,Computer science,Risk analysis (engineering),Artificial intelligence,Cluster analysis,Healthcare system,Database transaction,Health care,Disease,Software as a service,Guideline,Machine learning,Cloud computing | Conference |
Volume | ISBN | Citations |
2 | 978-1-5090-0391-4 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dingkun Li | 1 | 1 | 3.07 |
| Aziz Nasridinov | 2 | 49 | 14.32 |
| Hyun Woo Park | 3 | 12 | 5.15 |
| Keun Ho Ryu | 4 | 883 | 85.61 |