| Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging YW Park, J Oh, SC You, K Han, SS Ahn, YS Choi, JH Chang, SH Kim, ... European radiology, 1-9, 2019 | 148 | 2019 |
| Prediction of IDH1-mutation and 1p/19q-codeletion status using preoperative MR imaging phenotypes in lower grade gliomas YW Park, K Han, SS Ahn, S Bae, YS Choi, JH Chang, SH Kim, SG Kang, ... American Journal of Neuroradiology 39 (1), 37-42, 2018 | 140 | 2018 |
| Whole-tumor histogram and texture analyses of DTI for evaluation of IDH1-mutation and 1p/19q-codeletion status in World Health Organization grade II gliomas YW Park, K Han, SS Ahn, YS Choi, JH Chang, SH Kim, SG Kang, EH Kim, ... American Journal of Neuroradiology 39 (4), 693-698, 2018 | 68 | 2018 |
| Magnetic resonance imaging–visible perivascular spaces in basal ganglia predict cognitive decline in parkinson's disease YW Park, NY Shin, SJ Chung, J Kim, SM Lim, PH Lee, SK Lee, KJ Ahn Movement Disorders 34 (11), 1672-1679, 2019 | 65 | 2019 |
| Radiomics MRI phenotyping with machine learning to predict the grade of lower-grade gliomas: a study focused on nonenhancing tumors YW Park, YS Choi, SS Ahn, JH Chang, SH Kim, SK Lee Korean journal of radiology 20 (9), 1381, 2019 | 52 | 2019 |
| Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors Y Jun, T Eo, T Kim, H Shin, D Hwang, SH Bae, YW Park, HJ Lee, BW Choi, ... Scientific reports 8 (1), 9450, 2018 | 50 | 2018 |
| MRI features may predict molecular features of glioblastoma in isocitrate dehydrogenase wild-type lower-grade gliomas CJ Park, K Han, H Kim, SS Ahn, D Choi, YW Park, JH Chang, SH Kim, ... American Journal of Neuroradiology 42 (3), 448-456, 2021 | 42 | 2021 |
| Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model S Bae, HJ Lee, K Han, YW Park, YS Choi, SS Ahn, J Kim, SK Lee European radiology 27, 3353-3361, 2017 | 42 | 2017 |
| Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results C An, YW Park, SS Ahn, K Han, H Kim, SK Lee PloS one 16 (8), e0256152, 2021 | 40 | 2021 |
| Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional gradient echo imaging YW Park, Y Jun, Y Lee, K Han, C An, SS Ahn, D Hwang, SK Lee European radiology 31, 6686-6695, 2021 | 34 | 2021 |
| Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation YW Park, D Choi, JE Park, SS Ahn, H Kim, JH Chang, SH Kim, HS Kim, ... Scientific reports 11 (1), 2913, 2021 | 34 | 2021 |
| Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas YW Park, SS Ahn, CJ Park, K Han, EH Kim, SG Kang, JH Chang, SH Kim, ... European Radiology 30, 6475-6484, 2020 | 34 | 2020 |
| Differentiation of recurrent diffuse glioma from treatment-induced change using amide proton transfer imaging: incremental value to diffusion and perfusion parameters YW Park, SS Ahn, EH Kim, SG Kang, JH Chang, SH Kim, J Zhou, SK Lee Neuroradiology 63, 363-372, 2021 | 33 | 2021 |
| Diffusion tensor imaging radiomics in lower-grade glioma: improving subtyping of isocitrate dehydrogenase mutation status CJ Park, YS Choi, YW Park, SS Ahn, SG Kang, JH Chang, SH Kim, ... Neuroradiology 62 (3), 319-326, 2020 | 33 | 2020 |
| Quality reporting of radiomics analysis in mild cognitive impairment and Alzheimer's disease: a roadmap for moving forward SY Won, YW Park, M Park, SS Ahn, J Kim, SK Lee Korean Journal of Radiology 21 (12), 1345, 2020 | 32 | 2020 |
| Perivascular spaces in the basal ganglia and long-term motor prognosis in newly diagnosed Parkinson disease SJ Chung, HS Yoo, NY Shin, YW Park, HS Lee, JM Hong, YJ Kim, SK Lee, ... Neurology 96 (16), e2121-e2131, 2021 | 31 | 2021 |
| Radiomics model predicts granulation pattern in growth hormone-secreting pituitary adenomas YW Park, Y Kang, SS Ahn, CR Ku, EH Kim, SH Kim, EJ Lee, SH Kim, ... Pituitary 23, 691-700, 2020 | 31 | 2020 |
| Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls YW Park, YS Choi, SE Kim, D Choi, K Han, H Kim, SS Ahn, SA Kim, ... Scientific reports 10 (1), 19567, 2020 | 31 | 2020 |
| An interpretable multiparametric radiomics model for the diagnosis of schizophrenia using magnetic resonance imaging of the corpus callosum M Bang, J Eom, C An, S Kim, YW Park, SS Ahn, J Kim, SK Lee, SH Lee Translational psychiatry 11 (1), 462, 2021 | 29 | 2021 |
| Differentiating patients with schizophrenia from healthy controls by hippocampal subfields using radiomics YW Park, D Choi, J Lee, SS Ahn, SK Lee, SH Lee, M Bang Schizophrenia Research 223, 337-344, 2020 | 25 | 2020 |
