Ece Ateş Kuş

Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning–Based High-Dimensional Quantitative CT Texture Analysis in Predicting <i>PBRM1</i> Mutation Status

Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş et al. · American Journal of Roentgenology · 2019 · 113 citations

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

Burak Koçak, Ece Ateş Kuş, Emine Şebnem Durmaz et al. · European Radiology · 2019 · 81 citations

Urology, Image Analysis, Engineering +10

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

Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş et al. · American Journal of Roentgenology · 2019 · 81 citations

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

Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş et al. · European Radiology · 2019 · 65 citations

Neuro-oncology, Codeletion Status, Engineering +14

Reliability of Single-Slice–Based 2D CT Texture Analysis of Renal Masses: Influence of Intra- and Interobserver Manual Segmentation Variability on Radiomic Feature Reproducibility

Burak Koçak, Emine Şebnem Durmaz, Ozlem Korkmaz Kaya et al. · American Journal of Roentgenology · 2019 · 60 citations