Durmaz ES - Search Results

1

Predictive Factors for Rathke's Cleft Cyst Consistency.

Ozoner B, Aydin S, Akgun MY, Durmaz ES, Sahin S, Gazioglu N, Kizilkilic O, Kadioglu P, Tanriover N. Ozoner B, et al. Among authors: durmaz es. World Neurosurg. 2019 Aug;128:e522-e530. doi: 10.1016/j.wneu.2019.04.188. Epub 2019 Apr 30. World Neurosurg. 2019. PMID: 31048050

2

Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI.

Kocak B, Durmaz ES, Kadioglu P, Polat Korkmaz O, Comunoglu N, Tanriover N, Kocer N, Islak C, Kizilkilic O. Kocak B, et al. Among authors: durmaz es. Eur Radiol. 2019 Jun;29(6):2731-2739. doi: 10.1007/s00330-018-5876-2. Epub 2018 Nov 30. Eur Radiol. 2019. PMID: 30506213

3

Added Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Response to Somatostatin Analogs in Acromegaly Patients.

Durmaz ES, Kocak B, Kadioglu P, Comunoglu N, Ulu MO, Kocer N, Islak C, Kizilkilic O. Durmaz ES, et al. Turk Neurosurg. 2019;29(6):835-842. doi: 10.5137/1019-5149.JTN.26003-19.1. Turk Neurosurg. 2019. PMID: 30900736 Free article.

4

Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI.

Zeynalova A, Kocak B, Durmaz ES, Comunoglu N, Ozcan K, Ozcan G, Turk O, Tanriover N, Kocer N, Kizilkilic O, Islak C. Zeynalova A, et al. Among authors: durmaz es. Neuroradiology. 2019 Jul;61(7):767-774. doi: 10.1007/s00234-019-02211-2. Epub 2019 Apr 22. Neuroradiology. 2019. PMID: 31011772

5

Primary hypophysitis: Experience of a Single Tertiary Center.

Korkmaz OP, Sahin S, Ozkaya HM, Apaydin T, Durmaz ES, Haliloglu O, Durcan E, Kadioglu P. Korkmaz OP, et al. Among authors: durmaz es. Exp Clin Endocrinol Diabetes. 2021 Jan;129(1):14-21. doi: 10.1055/a-0919-4388. Epub 2019 Jun 24. Exp Clin Endocrinol Diabetes. 2021. PMID: 31234218

6

Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.

Kocak B, Durmaz ES, Ates E, Sel I, Turgut Gunes S, Kaya OK, Zeynalova A, Kilickesmez O. Kocak B, et al. Among authors: durmaz es. Eur Radiol. 2020 Feb;30(2):877-886. doi: 10.1007/s00330-019-06492-2. Epub 2019 Nov 5. Eur Radiol. 2020. PMID: 31691122

7

Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.

Kocak B, Durmaz ES, Ates E, Ulusan MB. Kocak B, et al. Among authors: durmaz es. AJR Am J Roentgenol. 2019 Mar;212(3):W55-W63. doi: 10.2214/AJR.18.20443. Epub 2019 Jan 2. AJR Am J Roentgenol. 2019. PMID: 30601030

8

Influence of segmentation margin on machine learning-based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas.

Kocak B, Ates E, Durmaz ES, Ulusan MB, Kilickesmez O. Kocak B, et al. Among authors: durmaz es. Eur Radiol. 2019 Sep;29(9):4765-4775. doi: 10.1007/s00330-019-6003-8. Epub 2019 Feb 12. Eur Radiol. 2019. PMID: 30747300

9

Increased vein wall thickness in Behçet disease.

Seyahi E, Gjoni M, Durmaz EŞ, Akbaş S, Sut N, Dikici AS, Mihmanli I, Yazici H. Seyahi E, et al. Among authors: durmaz es. J Vasc Surg Venous Lymphat Disord. 2019 Sep;7(5):677-684.e2. doi: 10.1016/j.jvsv.2018.11.006. Epub 2019 Feb 15. J Vasc Surg Venous Lymphat Disord. 2019. PMID: 30777674 Free article.

10

Unenhanced CT Texture Analysis of Clear Cell Renal Cell Carcinomas: A Machine Learning-Based Study for Predicting Histopathologic Nuclear Grade.

Kocak B, Durmaz ES, Ates E, Kaya OK, Kilickesmez O. Kocak B, et al. Among authors: durmaz es. AJR Am J Roentgenol. 2019 Jun;212(6):W132-W139. doi: 10.2214/AJR.18.20742. Epub 2019 Apr 11. AJR Am J Roentgenol. 2019. PMID: 30973779

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