Name
Abstract | ||
|---|---|---|
With the alarming increase in breast cancer cases, researchers have considered it a challenging research problem to propose dependable solutions. It is quite essential for early detection, prevention, and control against breast cancer. Existing schemes still does not utilize recent information technology support, and hence preventive measures and factors are also not appropriate. This paper adopts cloud computing to present association rule-based breast cancer prevention and control system. We have categorized our work into two phases. In phase 1 titled prevention and control, we propose item association rule (IAR) algorithm and N-IAR algorithm for n-item associations. It can be used to discover risk factors for breast cancer. Our algorithm discovers more risk factors than the traditional logistics method. Some factors which can be modified are used for breast cancer prevention and control. In addition, existing risk assessment models are not applicable to Chinese women as well. In phase 2, we manage this by introducing a new model based on machine learning. It utilizes real data from Chinese women and more risk factors for breast cancer. Moreover, we have identified and evaluated a number of new common risk factors. Results prove that our system achieves higher assessment values as compared to preliminaries. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/tcss.2019.2912629 | IEEE Transactions on Computational Social Systems |
Keywords | Field | DocType |
Breast cancer,Biological system modeling,Risk management,Machine learning,Control systems,Logistics | Breast cancer,Computer science,Information technology,Risk assessment,Association rule learning,Risk management,Artificial intelligence,Control system,Risk factors for breast cancer,Machine learning,Cloud computing | Journal |
Volume | Issue | ISSN |
6 | 5 | 2329-924X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ali Li | 1 | 0 | 1.69 |
| Liyuan Liu | 2 | 1 | 1.02 |
| Ata Ullah | 3 | 23 | 9.06 |
| Rui Wang | 4 | 111 | 22.06 |
| Jianhua Ma | 5 | 1401 | 148.82 |
| Runhe Huang | 6 | 407 | 56.46 |
| Zhigang Yu | 7 | 0 | 0.68 |
| Huansheng Ning | 8 | 847 | 83.48 |