| Radiomics with artificial intelligence: a practical guide for beginners B Koçak, EŞ Durmaz, E Ateş, Ö Kılıçkesmez Diagnostic and Interventional Radiology, 2019 | 359 | 2019 |
| CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII B Kocak, B Baessler, S Bakas, R Cuocolo, A Fedorov, L Maier-Hein, ... Insights into imaging 14 (1), 75, 2023 | 222 | 2023 |
| Endovascular treatment of carotid cavernous sinus fistula: a systematic review B Korkmazer, B Kocak, E Tureci, C Islak, N Kocer, O Kizilkilic World journal of radiology 5 (4), 143, 2013 | 202 | 2013 |
| Clear cell renal cell carcinoma: machine learning-based quantitative computed tomography texture analysis for prediction of fuhrman nuclear grade CT Bektas, B Kocak, AH Yardimci, MH Turkcanoglu, U Yucetas, SB Koca, ... European radiology 29, 1153-1163, 2019 | 160 | 2019 |
| Textural differences between renal cell carcinoma subtypes: Machine learning-based quantitative computed tomography texture analysis with independent external validation B Kocak, AH Yardimci, CT Bektas, MH Turkcanoglu, C Erdim, U Yucetas, ... European journal of radiology 107, 149-157, 2018 | 140 | 2018 |
| Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning–Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation … B Kocak, ES Durmaz, E Ates, MB Ulusan American Journal of Roentgenology 212 (3), W55-W63, 2019 | 116 | 2019 |
| METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII B Kocak, T Akinci D’Antonoli, N Mercaldo, A Alberich-Bayarri, B Baessler, ... Insights into Imaging 15 (1), 1-18, 2024 | 107 | 2024 |
| Flow Re-direction Endoluminal Device in treatment of cerebral aneurysms: initial experience with short-term follow-up results N Kocer, C Islak, O Kizilkilic, B Kocak, M Saglam, E Tureci Journal of neurosurgery 120 (5), 1158-1171, 2014 | 101 | 2014 |
| Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions TA D’Antonoli, A Stanzione, C Bluethgen, F Vernuccio, L Ugga, ... Diagnostic and Interventional Radiology 30 (2), 80, 2024 | 94 | 2024 |
| Influence of segmentation margin on machine learning–based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas B Kocak, E Ates, ES Durmaz, MB Ulusan, O Kilickesmez European radiology 29, 4765-4775, 2019 | 90 | 2019 |
| Early and midterm results of complex cerebral aneurysms treated with Silk stent M Velioglu, O Kizilkilic, H Selcuk, B Kocak, E Tureci, C Islak, N Kocer Neuroradiology 54, 1355-1365, 2012 | 79 | 2012 |
| Unenhanced CT Texture Analysis of Clear Cell Renal Cell Carcinomas: A Machine Learning–Based Study for Predicting Histopathologic Nuclear Grade B Kocak, ES Durmaz, E Ates, OK Kaya, O Kilickesmez American Journal of Roentgenology 212 (6), W132-W139, 2019 | 78 | 2019 |
| Prediction of benign and malignant solid renal masses: machine learning-based CT texture analysis C Erdim, AH Yardimci, CT Bektas, B Kocak, SB Koca, H Demir, ... Academic radiology 27 (10), 1422-1429, 2020 | 71 | 2020 |
| Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI A Zeynalova, B Kocak, ES Durmaz, N Comunoglu, K Ozcan, G Ozcan, ... Neuroradiology 61, 767-774, 2019 | 68 | 2019 |
| Radiogenomics of lower-grade gliomas: Machine learning–based MRI texture analysis for predicting 1p/19q codeletion status B Kocak, ES Durmaz, E Ates, I Sel, S Turgut Gunes, OK Kaya, ... European radiology 30, 877-886, 2020 | 67 | 2020 |
| Endovascular treatment of extracranial vertebral artery stenosis B Kocak, B Korkmazer, C Islak, N Kocer, O Kizilkilic World journal of radiology 4 (9), 391, 2012 | 65 | 2012 |
| Reliability of single-slice–based 2D CT texture analysis of renal masses: influence of intra-and interobserver manual segmentation variability on radiomic feature reproducibility B Kocak, ES Durmaz, OK Kaya, E Ates, O Kilickesmez American Journal of Roentgenology 213 (2), 377-383, 2019 | 62 | 2019 |
| Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI B Kocak, ES Durmaz, P Kadioglu, O Polat Korkmaz, N Comunoglu, ... European radiology 29, 2731-2739, 2019 | 61 | 2019 |
| How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts B Kocak, EA Kus, O Kilickesmez European Radiology 31, 1819-1830, 2021 | 52 | 2021 |
| Must-have qualities of clinical research on artificial intelligence and machine learning B Koçak, R Cuocolo, DP Dos Santos, A Stanzione, L Ugga Balkan Medical Journal 40 (1), 3, 2023 | 47 | 2023 |
Ozgur KILICKESMEZ, MD Prof of Inter...Basaksehir Cam and Sakura Hospital, University of Health Sciences, IstanbulVerifierad e-postadress på sbu.edu.tr
