Name
Abstract | ||
|---|---|---|
Melanoma is a serious cancer that causes many people to lose their lives. This disease can be diagnosed by a dermatologist as a result of interpretation of the dermoscopy images by the ABCD rule. In this study, a deep neural network (DNN) is used as a new method for diagnosis of melanoma skin cancer. This method is compared with the-state-art-methods in literature. According to the obtained results, DNN was more successful than the comparative methods. |
Year | Venue | Keywords |
|---|---|---|
2017 | Signal Processing and Communications Applications Conference | deep learning,deep neural network,ABCD rule,melanoma |
Field | DocType | ISSN |
Disease,Melanoma skin cancer,Pattern recognition,Computer science,Artificial intelligence,Melanoma,Dermatology,Artificial neural network,Cancer | Conference | 2165-0608 |
Citations | PageRank | References |
1 | 0.36 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alper Basturk | 1 | 124 | 11.43 |
| Mehmet Emin Yuksei | 2 | 1 | 0.36 |
| Badem, Hasan | 3 | 29 | 4.13 |
| Abdullah Caliskan | 4 | 23 | 2.04 |