| Amber 10 DA Case, TA Darden, TE Cheatham, CL Simmerling, J Wang, RE Duke, ... University of California, 2008 | 8584 | 2008 |
| AMBER 9 DA Case, TA Darden, TE Cheatham III, CL Simmerling, J Wang, RE Duke, ... University of California, San Francisco 45, 2006 | 3454 | 2006 |
| Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules D Hamelberg, J Mongan, JA McCammon The Journal of chemical physics 120 (24), 11919-11929, 2004 | 1648 | 2004 |
| Checklist for artificial intelligence in medical imaging (CLAIM): a guide for authors and reviewers J Mongan, L Moy, CE Kahn Jr Radiology: Artificial Intelligence 2 (2), e200029, 2020 | 725 | 2020 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 562 | 2021 |
| Constant pH molecular dynamics in generalized Born implicit solvent J Mongan, DA Case, JA McCammon Journal of computational chemistry 25 (16), 2038-2048, 2004 | 559 | 2004 |
| AMBER 10; University of California: San Francisco, 2008 DA Case, TA Darden, TE Cheatham III, CL Simmerling, J Wang, RE Duke, ... Google Scholar There is no corresponding record for this reference, 2008 | 508 | 2008 |
| AMBER 9; University of California: San Francisco, 2006 DA Case, TA Darden, TE Cheatham III, CL Simmerling, J Wang, RE Duke, ... Google Scholar There is no corresponding record for this reference, 9-174, 2014 | 496 | 2014 |
| Generalized Born model with a simple, robust molecular volume correction J Mongan, C Simmerling, JA McCammon, DA Case, A Onufriev Journal of chemical theory and computation 3 (1), 156-169, 2007 | 438 | 2007 |
| Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study AG Taylor, C Mielke, J Mongan PLoS medicine 15 (11), e1002697, 2018 | 199 | 2018 |
| Biomolecular simulations at constant pH J Mongan, DA Case Current opinion in structural biology 15 (2), 157-163, 2005 | 189 | 2005 |
| How far have we come? Artificial intelligence for chest radiograph interpretation K Kallianos, J Mongan, S Antani, T Henry, A Taylor, J Abuya, M Kohli Clinical radiology 74 (5), 338-345, 2019 | 188 | 2019 |
| AMBER 12 University of California DA Case, TA Darden, TE Cheatham, CL Simmerling, J Wang, RE Duke, ... San Francisco 1 (3), 2012 | 180 | 2012 |
| Construction of a machine learning dataset through collaboration: the RSNA 2019 brain CT hemorrhage challenge AE Flanders, LM Prevedello, G Shih, SS Halabi, J Kalpathy-Cramer, ... Radiology: Artificial Intelligence 2 (3), e190211, 2020 | 175 | 2020 |
| High-throughput classification of radiographs using deep convolutional neural networks A Rajkomar, S Lingam, AG Taylor, M Blum, J Mongan Journal of digital imaging 30, 95-101, 2017 | 161 | 2017 |
| The RSNA international COVID-19 open radiology database (RICORD) EB Tsai, S Simpson, MP Lungren, M Hershman, L Roshkovan, E Colak, ... Radiology 299 (1), E204-E213, 2021 | 140 | 2021 |
| AMBER, version 9 DA Case, TA Darden, TE Cheatham III, CL Simmerling, J Wang, RE Duke, ... University of California, San Francisco, 2006 | 135 | 2006 |
| AMBER, version 10 DA Case, TA Darden, TE Cheatham III, CL Simmerling, J Wang, RE Duke, ... University of California, San Francisco, CA, 2008 | 112 | 2008 |
| Limitations of atom-centered dielectric functions in implicit solvent models JMJ Swanson, J Mongan, JA McCammon The Journal of Physical Chemistry B 109 (31), 14769-14772, 2005 | 108 | 2005 |
| Interactive essential dynamics J Mongan Journal of computer-aided molecular design 18, 433-436, 2004 | 105 | 2004 |
