| 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 | 618 | 2021 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 234 | 2022 |
| Diagnosis of coronavirus disease 2019 pneumonia by using chest radiography: Value of artificial intelligence R Zhang, X Tie, Z Qi, NB Bevins, C Zhang, D Griner, TK Song, JD Nadig, ... Radiology 298 (2), E88-E97, 2021 | 144 | 2021 |
| Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance K Li, J Garrett, Y Ge, GH Chen Medical physics 41 (7), 071911, 2014 | 105 | 2014 |
| Diagnostic accuracy and failure mode analysis of a deep learning algorithm for the detection of cervical spine fractures AF Voter, ME Larson, JW Garrett, JPJ Yu American Journal of Neuroradiology 42 (8), 1550-1556, 2021 | 68 | 2021 |
| Diagnostic accuracy and failure mode analysis of a deep learning algorithm for the detection of intracranial hemorrhage AF Voter, E Meram, JW Garrett, JY John-Paul Journal of the American College of Radiology 18 (8), 1143-1152, 2021 | 65 | 2021 |
| Opportunistic Screening: Radiology Scientific Expert Panel PJ Pickhardt, RM Summers, JW Garrett, A Krishnaraj, S Agarwal, ... Radiology 307 (5), e222044, 2023 | 63 | 2023 |
| Grating based x-ray differential phase contrast imaging without mechanical phase stepping Y Ge, K Li, J Garrett, GH Chen Optics Express 22 (12), 14246-14252, 2014 | 63 | 2014 |
| Federated Learning used for predicting outcomes in SARS-COV-2 patients M Flores, I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, ... Research Square, 2021 | 55 | 2021 |
| Grating‐based phase contrast tomosynthesis imaging: proof‐of‐concept experimental studies K Li, Y Ge, J Garrett, N Bevins, J Zambelli, GH Chen Medical physics 41 (1), 011903, 2014 | 44 | 2014 |
| Fully automated deep learning tool for sarcopenia assessment on CT: L1 versus L3 vertebral level muscle measurements for opportunistic prediction of adverse clinical outcomes PJ Pickhardt, AA Perez, JW Garrett, PM Graffy, R Zea, RM Summers American Journal of Roentgenology 218 (1), 124-131, 2022 | 37 | 2022 |
| Deep learning CT-based quantitative visualization tool for liver volume estimation: defining normal and hepatomegaly AA Perez, V Noe-Kim, MG Lubner, PM Graffy, JW Garrett, DC Elton, ... Radiology 302 (2), 336-342, 2022 | 33 | 2022 |
| Abdominal CT body composition thresholds using automated AI tools for predicting 10-year adverse outcomes MH Lee, R Zea, JW Garrett, PM Graffy, RM Summers, PJ Pickhardt Radiology 306 (2), e220574, 2022 | 31 | 2022 |
| Improved CT-based osteoporosis assessment with a fully automated deep learning tool PJ Pickhardt, T Nguyen, AA Perez, PM Graffy, S Jang, RM Summers, ... Radiology: Artificial Intelligence 4 (5), e220042, 2022 | 31 | 2022 |
| Automated CT-based body composition analysis: a golden opportunity PJ Pickhardt, RM Summers, JW Garrett Korean Journal of Radiology 22 (12), 1934, 2021 | 27 | 2021 |
| Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs A Pyrros, SM Borstelmann, R Mantravadi, Z Zaiman, K Thomas, B Price, ... Nature communications 14 (1), 4039, 2023 | 24 | 2023 |
| Reduced anatomical clutter in digital breast tomosynthesis with statistical iterative reconstruction JW Garrett, Y Li, K Li, GH Chen Medical physics 45 (5), 2009-2022, 2018 | 23 | 2018 |
| Correlation between human observer performance and model observer performance in differential phase contrast CT K Li, J Garrett, GH Chen Medical physics 40 (11), 111905, 2013 | 23 | 2013 |
| Quantitative lung perfusion blood volume using dual energy CT–based effective atomic number (Zeff) imaging K Li, Y Li, Z Qi, JW Garrett, TM Grist, GH Chen Medical physics 48 (11), 6658-6672, 2021 | 21 | 2021 |
| Reduction of beam hardening artifacts in cone-beam CT imaging via SMART-RECON algorithm Y Li, J Garrett, GH Chen Proceedings of SPIE--the International Society for Optical Engineering 9783, 2016 | 20 | 2016 |
Guang-Hong ChenCharles A. Mistretta Professor of Medical Physics and Radiology, University of Wisconsin-Madisonwisc.edu의 이메일 확인됨