| Super‐resolution musculoskeletal MRI using deep learning AS Chaudhari, Z Fang, F Kogan, J Wood, KJ Stevens, EK Gibbons, ... Magnetic resonance in medicine 80 (5), 2139-2154, 2018 | 368 | 2018 |
| OpenCap: Human movement dynamics from smartphone videos SD Uhlrich, A Falisse, Ł Kidziński, J Muccini, M Ko, AS Chaudhari, ... PLoS computational biology 19 (10), e1011462, 2023 | 125 | 2023 |
| Self-supervised learning for medical image classification: a systematic review and implementation guidelines SC Huang, A Pareek, M Jensen, MP Lungren, S Yeung, AS Chaudhari NPJ Digital Medicine 6 (1), 74, 2023 | 100 | 2023 |
| TorchXRayVision: A library of chest X-ray datasets and models JP Cohen, JD Viviano, P Bertin, P Morrison, P Torabian, M Guarrera, ... International Conference on Medical Imaging with Deep Learning, 231-249, 2022 | 95 | 2022 |
| A simple analytic method for estimating T2 in the knee from DESS B Sveinsson, AS Chaudhari, GE Gold, BA Hargreaves Magnetic resonance imaging 38, 63-70, 2017 | 87 | 2017 |
| Adapted large language models can outperform medical experts in clinical text summarization D Van Veen, C Van Uden, L Blankemeier, JB Delbrouck, A Aali, ... Nature medicine 30 (4), 1134-1142, 2024 | 85* | 2024 |
| Measuring robustness in deep learning based compressive sensing MZ Darestani, AS Chaudhari, R Heckel International Conference on Machine Learning, 2433-2444, 2021 | 84 | 2021 |
| Adapting pretrained vision-language foundational models to medical imaging domains P Chambon, C Bluethgen, CP Langlotz, A Chaudhari arXiv preprint arXiv:2210.04133, 2022 | 79 | 2022 |
| Five‐minute knee MRI for simultaneous morphometry and T2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double … AS Chaudhari, MS Black, S Eijgenraam, W Wirth, S Maschek, ... Journal of Magnetic Resonance Imaging 47 (5), 1328-1341, 2018 | 78 | 2018 |
| Prospective deployment of deep learning in MRI: a framework for important considerations, challenges, and recommendations for best practices AS Chaudhari, CM Sandino, EK Cole, DB Larson, GE Gold, ... Journal of Magnetic Resonance Imaging 54 (2), 357-371, 2021 | 76 | 2021 |
| Roentgen: vision-language foundation model for chest x-ray generation P Chambon, C Bluethgen, JB Delbrouck, R Van der Sluijs, M Połacin, ... arXiv preprint arXiv:2211.12737, 2022 | 72 | 2022 |
| Simultaneous NODDI and GFA parameter map generation from subsampled q‐space imaging using deep learning EK Gibbons, KK Hodgson, AS Chaudhari, LG Richards, JJ Majersik, ... Magnetic resonance in medicine 81 (4), 2399-2411, 2019 | 71 | 2019 |
| Utility of deep learning super‐resolution in the context of osteoarthritis MRI biomarkers AS Chaudhari, KJ Stevens, JP Wood, AK Chakraborty, EK Gibbons, ... Journal of Magnetic Resonance Imaging 51 (3), 768-779, 2020 | 56 | 2020 |
| The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset AD Desai, F Caliva, C Iriondo, A Mortazi, S Jambawalikar, U Bagci, ... Radiology: Artificial Intelligence 3 (3), e200078, 2021 | 55 | 2021 |
| Rapid knee MRI acquisition and analysis techniques for imaging osteoarthritis AS Chaudhari, F Kogan, V Pedoia, S Majumdar, GE Gold, BA Hargreaves Journal of Magnetic Resonance Imaging 52 (5), 1321-1339, 2020 | 55 | 2020 |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, ... Nature machine intelligence 5 (7), 799-810, 2023 | 53* | 2023 |
| Imaging and T2 relaxometry of short‐T2 connective tissues in the knee using ultrashort echo‐time double‐echo steady‐state (UTEDESS) AS Chaudhari, B Sveinsson, CJ Moran, EJ McWalter, EM Johnson, ... Magnetic resonance in medicine 78 (6), 2136-2148, 2017 | 51 | 2017 |
| Low-count whole-body PET with deep learning in a multicenter and externally validated study AS Chaudhari, E Mittra, GA Davidzon, P Gulaka, H Gandhi, A Brown, ... NPJ digital medicine 4 (1), 127, 2021 | 50 | 2021 |
| Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain J Kemnitz, CF Baumgartner, F Eckstein, A Chaudhari, A Ruhdorfer, ... Magnetic Resonance Materials in Physics, Biology and Medicine 33, 483-493, 2020 | 50 | 2020 |
| Evaluation of a flexible 12-channel screen-printed pediatric MRI coil SA Winkler, J Corea, B Lechêne, K O’Brien, JR Bonanni, A Chaudhari, ... Radiology 291 (1), 180-185, 2019 | 50 | 2019 |
Garry GoldProfessor of Radiology, Stanford University在 stanford.edu 的电子邮件经过验证
