Name
Title | ||
|---|---|---|
Improving Accuracy of Non-invasive Hemoglobin Monitors: A Functional Regression Model for Streaming SpHb Data. |
Abstract | ||
|---|---|---|
Accurate prediction of current and future HgB levels can lead to sophisticated decision models that determine the optimal timing and amount of blood product transfusions. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TBME.2018.2856091 | IEEE transactions on bio-medical engineering |
Keywords | Field | DocType |
Standards,Gold,Current measurement,Monitoring,Biomedical monitoring,Measurement uncertainty | Spline (mathematics),Computer vision,Computer science,Functional regression,Mean absolute error,Measurement uncertainty,Algorithm,Decision model,Artificial intelligence,Smoothness,Care protocols | Journal |
Volume | Issue | ISSN |
66 | 3 | 1558-2531 |
Citations | PageRank | References |
1 | 0.43 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Devashish Das | 1 | 5 | 1.92 |
| Kalyan S. Pasupathy | 2 | 21 | 9.19 |
| Nadeem N Haddad | 3 | 1 | 0.43 |
| Hallbeck M Susan | 4 | 4 | 2.58 |
| Martin D Zielinski | 5 | 1 | 0.43 |
| Mustafa Sir | 6 | 42 | 9.57 |