Name
Title | ||
|---|---|---|
Pattern Recognition and Prognostic Analysis of Longitudinal Blood Pressure Records in Hemodialysis Treatment Based on a Convolutional Neural Network. |
Abstract | ||
|---|---|---|
•We classify ESRD patients based on dense sequences in EHR data.•We suggest an approach to identify and visualize intradialytic systolic BP patterns.•We first proposed the concept of multiple session patterns of intradialytic blood pressure.•We demonstrate that models with multiple session patterns have a better prediction of patients’ 1-year survival. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jbi.2019.103271 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Hemodialysis,Intradialytic blood pressure patterns,Convolutional neural network,Global average pooling,Two-phase training | Hemodialysis,Pattern recognition,Convolutional neural network,Convolution,Computer science,Data imbalance,Artificial intelligence,Blood pressure,Deep learning,Kernel (image processing),Continuous hemodialysis | Journal |
Volume | ISSN | Citations |
98 | 1532-0464 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Wang | 1 | 2 | 2.58 |
| Yu Wang | 2 | 167 | 15.47 |
| Yu Tian | 3 | 3 | 3.11 |
| Ping Zhang | 4 | 0 | 1.01 |
| Jianghua Chen | 5 | 1 | 2.05 |
| Jing-Song Li | 6 | 222 | 11.02 |