Name
Title | ||
|---|---|---|
A Unified Hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign |
Abstract | ||
|---|---|---|
•A unified Hierachical XGBoost model for classifying priorities for COVID-19 vaccination campaign.•Avoiding bias in the learning procedure.•Experimental results on a novel FIMMG_COVID EHR dataset.•High predictive performances and model interpretability.•Integration in a CDSS for supporting the GPs for assigning COVID-19 vaccine administration priorities. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.patcog.2021.108197 | Pattern Recognition |
Keywords | DocType | Volume |
COVID-19,Vaccination,Machine learning,XGBoost,Clinical decision support system,Model interpretability | Journal | 121 |
Issue | ISSN | Citations |
1 | 0031-3203 | 1 |
PageRank | References | Authors |
0.35 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| luca romeo | 1 | 21 | 9.59 |
| Emanuele Frontoni | 2 | 248 | 47.04 |