Y. S. SALİHOĞLU Et Al. , "Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules," MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2, pp.82-88, 2022
SALİHOĞLU, Y. S. Et Al. 2022. Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules. MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2 , 82-88.
SALİHOĞLU, Y. S., Erdemir, R. U., Puren, B. A., ÖZDEMİR, S., Uyulan, C., ERGÜZEL, T. T., ... Tekin, H. O.(2022). Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules. MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2, 82-88.
SALİHOĞLU, YAVUZ Et Al. "Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules," MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2, 82-88, 2022
SALİHOĞLU, YAVUZ S. Et Al. "Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules." MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2, pp.82-88, 2022
SALİHOĞLU, Y. S. Et Al. (2022) . "Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules." MOLECULAR IMAGING AND RADIONUCLIDE THERAPY , vol.31, no.2, pp.82-88.
@article{article, author={YAVUZ SAMİ SALİHOĞLU Et Al. }, title={Diagnostic Performance of Machine Learning Models Based on F-18-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules}, journal={MOLECULAR IMAGING AND RADIONUCLIDE THERAPY}, year=2022, pages={82-88} }