Name
Title | ||
|---|---|---|
Automatic method for classifying COVID-19 patients based on chest X-ray images, using deep features and PSO-optimized XGBoost |
Abstract | ||
|---|---|---|
•A method to classify patients in COVID-19 or non-COVID-19 based on Chest X-Rays.•We introduce a deep features extraction with XGBoost optimized by PSO.•The method was developed and tested on two public databases.•We evaluate our work in 1547 CXR images.•The method achieved an accuracy of 98.71%, precision of 98.89%, recall of 99.63%, and F1-score of 99.25%. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.115452 | Expert Systems with Applications |
Keywords | DocType | Volume |
Chest X-Rays,COVID-19,Deep features,Medical images,Particle swarm optimization,Extreme gradient boosting | Journal | 183 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
8 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Domingos Alves Dias Júnior | 1 | 0 | 0.34 |
| Luana Batista da Cruz | 2 | 3 | 2.74 |
| João Otávio Bandeira Diniz | 3 | 19 | 4.29 |
| Giovanni Lucca França da Silva | 4 | 16 | 2.99 |
| Geraldo Braz Junior | 5 | 76 | 15.10 |
| Aristofanes C. Silva | 6 | 316 | 36.48 |
| Anselmo C. Paiva | 7 | 379 | 48.88 |
| Rodolfo Acatauassú Nunes | 8 | 57 | 4.45 |
| Marcelo Gattass | 9 | 382 | 48.43 |