| dc.contributor.author | Akan, Aydin | |
| dc.contributor.author | Tartar, Ahmet | |
| dc.date.accessioned | 2021-03-04T13:38:49Z | |
| dc.date.available | 2021-03-04T13:38:49Z | |
| dc.identifier.citation | Tartar A., Akan A., "Performance of Ensemble Learning Classifiers on Malignant-Benign Classification of Pulmonary Nodules", 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Türkiye, 23 - 25 Nisan 2014, ss.722-725 | |
| dc.identifier.other | vv_1032021 | |
| dc.identifier.other | av_7d820bbd-4a66-4257-a417-e705e11fdb48 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12627/85742 | |
| dc.identifier.uri | https://doi.org/10.1109/siu.2014.6830331 | |
| dc.description.abstract | Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this study, a novel Computer-aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. Proposed CAD system, providing an important support to radiologists at the diagnosis process of the disease, achieves high classification performance using ensemble learning classifiers. | |
| dc.language.iso | eng | |
| dc.subject | Mühendislik ve Teknoloji | |
| dc.subject | Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği | |
| dc.subject | Sinyal İşleme | |
| dc.subject | TELEKOMÜNİKASYON | |
| dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
| dc.subject | Mühendislik | |
| dc.subject | MÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK | |
| dc.title | Performance of Ensemble Learning Classifiers on Malignant-Benign Classification of Pulmonary Nodules | |
| dc.type | Bildiri | |
| dc.contributor.department | İstanbul Üniversitesi , , | |
| dc.contributor.firstauthorID | 143311 | |
