Name
Title | ||
|---|---|---|
Network-Based Prediction of Major Adverse Cardiac Events in Acute Coronary Syndromes from Imbalanced EMR Data. |
Abstract | ||
|---|---|---|
The low proportion and the rapid evolvement of major adverse cardiac events (MACE) present challenges for predicting MACE by machine learning models. In this paper, we propose a method to predict MACE from large-scale imbalanced EMR data by using a network-based one-class classifier. It only used the reliably known MACE samples to establish the hyperspherical model. Experiments show that our model outperforms the state-of-the-art models. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/SHTI190494 | Studies in Health Technology and Informatics |
Keywords | DocType | Volume |
Acute coronary syndrome,machine learning,algorithms | Conference | 264 |
ISSN | Citations | PageRank |
0926-9630 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pengwei Hu | 1 | 3 | 4.78 |
| Eryu Xia | 2 | 8 | 4.14 |
| Shochun Li | 3 | 0 | 0.68 |
| Xin Du | 4 | 127 | 26.78 |
| Changsheng Ma | 5 | 2 | 2.06 |
| Jianzeng Dong | 6 | 1 | 2.05 |
| Keith C. C. Chan | 7 | 983 | 108.02 |