| Yazarlar (1) |
Dr. Öğr. Üyesi Kadir Can BURÇAK
Kırşehir Ahi Evran Üniversitesi, Türkiye |
| Özet |
| Breast cancer begins in the breast tissue when mutated cells grow out of control and eventually form a tumor. One of the most common causes of death among women worldwide is breast cancer. Early diagnosis and treatment can increase the likelihood of cancer prevention and recovery. Breast ultrasound analysis performed by medical professionals requires high competence in interpreting images, is time-consuming, and creates a negative situation in terms of the treatment process. Artificial intelligence methods have shown great success in the development of medical diagnosis and diagnostic models. When combined with artificial intelligence techniques, breast ultrasound images can produce good results in the detection and classification of breast cancer. This study focused on multiclass classification of breast cancer ultrasound images collected via ultrasound scanning via deep learning methods. In the first … |
| Anahtar Kelimeler |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Neural Computing and Applications |
| Dergi ISSN | 0941-0643 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | İngilizce |
| Basım Tarihi | 09-2025 |
| Cilt No | 37 |
| DOI Numarası | 10.1007/s00521-025-11653-0 |
| Makale Linki | https://doi.org/10.1007/s00521-025-11653-0 |
| Atıf Sayıları |
