Name
Abstract | ||
|---|---|---|
This paper uses a set of 3D geometric measures with the purpose of characterizing lung nodules as malignant or benign. Based on a sample of 36 nodules, 29 benign and 7 malignant, these measures are analyzed with a technique for classification and analysis called reforcement learning. We have concluded that this techinique allows good discrimination from benign to malignant nodules. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11510888_29 | MLDM |
Keywords | Field | DocType |
lung nodule,good discrimination,reforcement learning,geometric measure,malignant nodule,reinforcement learning | Pattern recognition,Lung,Computer science,Artificial intelligence,Machine learning,Reinforcement learning | Conference |
Volume | ISSN | ISBN |
3587 | 0302-9743 | 3-540-26923-1 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aristofanes C. Silva | 1 | 316 | 36.48 |
| Valdeci Ribeiro da Silva | 2 | 0 | 0.34 |
| Areolino de Almeida Neto | 3 | 5 | 2.84 |
| Anselmo C. Paiva | 4 | 379 | 48.88 |