| A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain Y Ding, JH Sohn, MG Kawczynski, H Trivedi, R Harnish, NW Jenkins, ... Radiology 290 (2), 456-464, 2019 | 638 | 2019 |
| Development and validation of deep learning–based automatic detection algorithm for malignant pulmonary nodules on chest radiographs JG Nam, S Park, EJ Hwang, JH Lee, KN Jin, KY Lim, TH Vu, JH Sohn, ... Radiology 290 (1), 218-228, 2019 | 528 | 2019 |
| Federated learning for predicting clinical outcomes in patients with COVID-19 I Dayan, HR Roth, A Zhong, A Harouni, A Gentili, AZ Abidin, A Liu, ... Nature medicine 27 (10), 1735-1743, 2021 | 527 | 2021 |
| Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ... JAMA network open 3 (3), e200265-e200265, 2020 | 366 | 2020 |
| Automatic hip fracture identification and functional subclassification with deep learning JD Krogue, KV Cheng, KM Hwang, P Toogood, EG Meinberg, EJ Geiger, ... Radiology: Artificial Intelligence 2 (2), e190023, 2020 | 134 | 2020 |
| Comparison of existing response criteria in patients with hepatocellular carcinoma treated with transarterial chemoembolization using a 3D quantitative approach V Tacher, MD Lin, R Duran, H Yarmohammadi, H Lee, J Chapiro, M Chao, ... Radiology 278 (1), 275-284, 2016 | 124 | 2016 |
| Automatic determination of the need for intravenous contrast in musculoskeletal MRI examinations using IBM Watson’s natural language processing algorithm H Trivedi, J Mesterhazy, B Laguna, T Vu, JH Sohn Journal of digital imaging 31, 245-251, 2018 | 95 | 2018 |
| Development and validation of a multitask deep learning model for severity grading of hip osteoarthritis features on radiographs CE von Schacky, JH Sohn, F Liu, E Ozhinsky, PM Jungmann, L Nardo, ... Radiology 295 (1), 136-145, 2020 | 77 | 2020 |
| Class 3 semaphorin mediates dendrite growth in adult newborn neurons through Cdk5/FAK pathway T Ng, JR Ryu, JH Sohn, T Tan, H Song, G Ming, ELK Goh PloS one 8 (6), e65572, 2013 | 66 | 2013 |
| Imaging biomarkers of tumor response in neuroendocrine liver metastases treated with transarterial chemoembolization: can enhancing tumor burden of the whole liver help predict … S Sahu, R Schernthaner, R Ardon, J Chapiro, Y Zhao, JH Sohn, ... Radiology 283 (3), 883-894, 2017 | 60 | 2017 |
| Quality initiatives: statistical control charts: simplifying the analysis of data for quality improvement YY Cheung, B Jung, JH Sohn, G Ogrinc Radiographics 32 (7), 2113-2126, 2012 | 54 | 2012 |
| Validation of the Hong Kong Liver Cancer Staging System in determining prognosis of the North American patients following intra-arterial therapy JH Sohn, R Duran, Y Zhao, F Fleckenstein, J Chapiro, S Sahu, ... Clinical Gastroenterology and Hepatology 15 (5), 746-755. e4, 2017 | 44 | 2017 |
| CT-less direct correction of attenuation and scatter in the image space using deep learning for whole-body FDG PET: potential benefits and pitfalls J Yang, JH Sohn, SC Behr, GT Gullberg, Y Seo Radiology: Artificial Intelligence 3 (2), e200137, 2020 | 41 | 2020 |
| Conformal language modeling V Quach, A Fisch, T Schuster, A Yala, JH Sohn, TS Jaakkola, R Barzilay arXiv preprint arXiv:2306.10193, 2023 | 39 | 2023 |
| Transarterial chemoembolization for the treatment of advanced-stage hepatocellular carcinoma Y Zhao, R Duran, J Chapiro, JH Sohn, S Sahu, F Fleckenstein, S Smolka, ... Journal of Gastrointestinal Surgery 20 (12), 2002-2009, 2016 | 37 | 2016 |
| An open-source, vender agnostic hardware and software pipeline for integration of artificial intelligence in radiology workflow JH Sohn, YR Chillakuru, S Lee, AY Lee, T Kelil, CP Hess, Y Seo, T Vu, ... Journal of digital imaging 33, 1041-1046, 2020 | 34 | 2020 |
| Multimodality imaging of ethiodized oil–loaded radiopaque microspheres during transarterial embolization of rabbits with VX2 liver tumors V Tacher, R Duran, MD Lin, JH Sohn, KV Sharma, Z Wang, J Chapiro, ... Radiology 279 (3), 741-753, 2016 | 34 | 2016 |
| Radiologic-pathologic analysis of quantitative 3D tumour enhancement on contrast-enhanced MR imaging: a study of ROI placement A Chockalingam, R Duran, JH Sohn, R Schernthaner, J Chapiro, H Lee, ... European radiology 26, 103-113, 2016 | 34 | 2016 |
| 3D Quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of … FN Fleckenstein, RE Schernthaner, R Duran, JH Sohn, S Sahu, Y Zhao, ... European radiology 26, 3243-3252, 2016 | 33 | 2016 |
| Large scale semi-automated labeling of routine free-text clinical records for deep learning HM Trivedi, M Panahiazar, A Liang, D Lituiev, P Chang, JH Sohn, ... Journal of digital imaging 32, 30-37, 2019 | 23 | 2019 |
Youngho SeoUniversity of California, San Francisco and Berkeley在 ucsf.edu 的电子邮件经过验证
