Name
Abstract | ||
|---|---|---|
With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machine-learning techniques demonstrated their applications in healthcare to answer several questions, there is still room for improvement in every aspect. In this paper, we are demonstrating a method that improves the performance of a delirium prediction model using random forest in combination with logistic regression. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/SHTI190537 | Studies in Health Technology and Informatics |
Keywords | DocType | Volume |
Algorithms,Delirium,Logistic Models | Conference | 264 |
ISSN | Citations | PageRank |
0926-9630 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sai Pavan Kumar Veeranki | 1 | 0 | 1.01 |
| Dieter Hayn | 2 | 28 | 9.62 |
| Stefanie Jauk | 3 | 0 | 2.03 |
| Franz Quehenberger | 4 | 0 | 0.34 |
| Diether Kramer | 5 | 1 | 2.41 |
| W Leodolter | 6 | 7 | 4.64 |
| Günter Schreier | 7 | 56 | 23.73 |