| Classification of the glioma grading using radiomics analysis H Cho, S Lee, J Kim, H Park PeerJ 6, e5982, 2018 | 186 | 2018 |
| Predicting survival using pretreatment CT for patients with hepatocellular carcinoma treated with transarterial chemoembolization: comparison of models using radiomics J Kim, SJ Choi, SH Lee, HY Lee, H Park American Journal of Roentgenology, 1026-1034, 2018 | 111 | 2018 |
| Imaging phenotyping using radiomics to predict micropapillary pattern within lung adenocarcinoma SH Song, H Park, G Lee, HY Lee, I Sohn, HS Kim, SH Lee, JY Jeong, ... Journal of Thoracic Oncology 12 (4), 624-632, 2017 | 101 | 2017 |
| Radiomics in breast imaging from techniques to clinical applications: a review SH Lee, H Park, ES Ko Korean journal of radiology 21 (7), 779, 2020 | 93 | 2020 |
| Deciphering the tumor microenvironment through radiomics in non-small cell lung cancer: Correlation with immune profiles HJ Yoon, J Kang, H Park, I Sohn, SH Lee, HY Lee PloS one 15 (4), e0231227, 2020 | 58 | 2020 |
| Clinical impact of variability on CT radiomics and suggestions for suitable feature selection: a focus on lung cancer SH Lee, H Cho, HY Lee, H Park Cancer Imaging 19, 1-12, 2019 | 49 | 2019 |
| DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs B Park, MJ Lee, S Lee, J Cha, CS Chung, ST Kim, H Park NeuroImage: Clinical 18, 638-647, 2018 | 31 | 2018 |
| Comprehensive computed tomography radiomics analysis of lung adenocarcinoma for prognostication G Lee, H Park, I Sohn, SH Lee, SH Song, H Kim, KS Lee, YM Shim, ... The oncologist 23 (7), 806-813, 2018 | 30 | 2018 |
| Imaging genetics approach to Parkinson’s disease and its correlation with clinical score M Kim, J Kim, SH Lee, H Park Scientific reports 7 (1), 46700, 2017 | 26 | 2017 |
| Functional connectivity of child and adolescent attention deficit hyperactivity disorder patients: correlation with IQ B Park, J Hong, SH Lee, H Park Frontiers in Human Neuroscience 10, 565, 2016 | 23 | 2016 |
| Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics HJ Yoon, H Park, HY Lee, I Sohn, J Ahn, SH Lee Thoracic cancer 11 (9), 2600-2609, 2020 | 21 | 2020 |
| Measurement variability in treatment response determination for non–small cell lung cancer: improvements using radiomics G Lee, SH Bak, HY Lee, JY Choi, H Park, SH Lee, Y Ohno, M Nishino, ... Journal of Thoracic Imaging 34 (2), 103-115, 2019 | 21 | 2019 |
| Clustering approach to identify intratumour heterogeneity combining FDG PET and diffusion-weighted MRI in lung adenocarcinoma J Kim, SY Ryu, SH Lee, HY Lee, H Park European radiology 29, 468-475, 2019 | 21 | 2019 |
| Prognostic impact of longitudinal monitoring of radiomic features in patients with advanced non-small cell lung cancer SH Bak, H Park, I Sohn, SH Lee, MJ Ahn, HY Lee Scientific Reports 9 (1), 8730, 2019 | 20 | 2019 |
| Differences in early and late mild cognitive impairment tractography using a diffusion tensor MRI S Lee, J Seo, J Lee, H Park Neuroreport 25 (17), 1393-1398, 2014 | 17 | 2014 |
| Are radiomics features universally applicable to different organs? SH Lee, H Cho, J Kwon, HY Lee, H Park Cancer Imaging 21, 1-10, 2021 | 16 | 2021 |
| Deciphering clinicoradiologic phenotype for thymidylate synthase expression status in patients with advanced lung adenocarcinoma using a radiomics approach SW Lee, H Park, HY Lee, I Sohn, SH Lee, J Kang, JM Sun, MJ Ahn Scientific Reports 8 (1), 8968, 2018 | 12 | 2018 |
| Robust multimodal fusion network using adversarial learning for brain tumor grading S Jeong, H Cho, S Lee, H Park Computer Methods and Programs in Biomedicine 226, 107165, 2022 | 9 | 2022 |
| Parallel comparison and combining effect of radiomic and emerging genomic data for prognostic stratification of non‐small cell lung carcinoma patients KH Kim, J Kim, H Park, H Kim, S Lee, I Sohn, HY Lee, WY Park Thoracic cancer 11 (9), 2542-2551, 2020 | 9 | 2020 |
| Parametric response mapping of longitudinal PET scans and their use in detecting changes in Alzheimer’s diseases S Lee, H Park, ADNI Biomedical Engineering Letters 4, 73-79, 2014 | 8 | 2014 |