Name
Title | ||
|---|---|---|
Predicting the morbidity of chronic obstructive pulmonary disease based on multiple locally weighted linear regression model with K-means clustering. |
Abstract | ||
|---|---|---|
•We investigated the relationship between air pollution and the occurrence of COPD acute exacerbation.•PM2.5 and SO2 are the most important factors contributing to improving the prediction accuracy of our model.•Multiple locally weighted linear regression algorithm is used to build prediction model.•Use of k-means algorithm in data training can improve the prediction accuracy.•The result demonstrated minimum prediction error through comparing with several regression models. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ijmedinf.2020.104141 | International Journal of Medical Informatics |
Keywords | DocType | Volume |
Chronic obstructive pulmonary disease,K-means clustering,Locally weighted linear regression,PM2.5,SO2 | Journal | 139 |
ISSN | Citations | PageRank |
1386-5056 | 1 | 0.63 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhi-Yong Huang | 1 | 2 | 2.33 |
| Shuang Lin | 2 | 1 | 0.63 |
| Li-Li Long | 3 | 1 | 0.63 |
| Jiao-Yang Cao | 4 | 1 | 0.63 |
| Fen Luo | 5 | 1 | 0.63 |
| Wen-Cheng Qin | 6 | 1 | 0.63 |
| Da-Ming Sun | 7 | 1 | 0.63 |
| Hans Gregersen | 8 | 5 | 1.59 |