Name
Abstract | ||
|---|---|---|
•A new software to Parkinson’s diagnosis was developed.•Three machine learning algorithms (SVM, OPF, and Bayesian classifier) were compared.•An experimental evaluation with 20 patients were made. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.patrec.2019.04.003 | Pattern Recognition Letters |
Keywords | Field | DocType |
Parkinson’s disease,machine learning,image processing | Parkinson's disease,Disease,Naive Bayes classifier,Pattern recognition,Support vector machine,Dopamine,Substantia nigra,Medical history,Artificial intelligence,Mathematics | Journal |
Volume | ISSN | Citations |
125 | 0167-8655 | 1 |
PageRank | References | Authors |
0.38 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucas S. Bernardo | 1 | 1 | 0.38 |
| Angeles Quezada | 2 | 1 | 0.72 |
| Roberto Muñoz | 3 | 43 | 10.46 |
| Fernanda Martins Maia | 4 | 1 | 0.38 |
| Clayton Pereira | 5 | 82 | 8.52 |
| Wanqing Wu | 6 | 126 | 13.77 |
| Victor Hugo C. de Albuquerque | 7 | 914 | 83.30 |