| CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning NAY Rajpurkar P, Irvin J, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A ... arXiv:1711.05225, 2017 | 3570* | 2017 |
| Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison J Irvin, P Rajpurkar, M Ko, Y Yu, S Ciurea-Ilcus, C Chute, H Marklund, ... Thirty-Third AAAI Conference on Artificial Intelligence, 2019 | 3006 | 2019 |
| Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists P Rajpurkar, J Irvin, RL Ball, K Zhu, B Yang, H Mehta, T Duan, D Ding, ... PLoS medicine 15 (11), e1002686, 2018 | 1313 | 2018 |
| Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet N Bien, P Rajpurkar, RL Ball, J Irvin, A Park, E Jones, M Bereket, BN Patel, ... PLoS medicine 15 (11), e1002699, 2018 | 702 | 2018 |
| Mura dataset: Towards radiologist-level abnormality detection in musculoskeletal radiographs P Rajpurkar, J Irvin, A Bagul, D Ding, T Duan, H Mehta, B Yang, K Zhu, ... | 460* | 2018 |
| MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs NAY Rajpurkar P, Irvin J, Bagul A, Ding D, Duan T, Mehta H, Yang B, Zhu K ... arXiv:1712.06957, 2017 | 390* | 2017 |
| Impact of a deep learning assistant on the histopathologic classification of liver cancer A Kiani, B Uyumazturk, P Rajpurkar, A Wang, R Gao, E Jones, Y Yu, ... NPJ digital medicine 3 (1), 23, 2020 | 262 | 2020 |
| Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model JAMA Network Open 2 (6), e195600-e195600, 2019 | 255 | 2019 |
| Deep learning to classify radiology free-text reports MC Chen, RL Ball, L Yang, N Moradzadeh, BE Chapman, DB Larson, ... Radiology 286 (3), 845-852, 2017 | 247 | 2017 |
| 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 | 218 | 2020 |
| PENet-A Scalable Deep-Learning Model for Automated Diagnosis of Pulmonary Embolism Using Volumetric CT Imaging SC Huang, T Kothari, I Banerjee, C Chute, RL Ball, N Borus, A Huang, ... Available at SSRN 3384889, 2019 | 149 | 2019 |
| PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging SC Huang, T Kothari, I Banerjee, C Chute, RL Ball, N Borus, A Huang, ... NPJ digital medicine 3 (1), 61, 2020 | 146 | 2020 |
| CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV P Rajpurkar, C O’Connell, A Schechter, N Asnani, J Li, A Kiani, RL Ball, ... NPJ digital medicine 3 (1), 115, 2020 | 126 | 2020 |
| The RSNA pulmonary embolism CT dataset E Colak, FC Kitamura, SB Hobbs, CC Wu, MP Lungren, LM Prevedello, ... Radiology: Artificial Intelligence 3 (2), e200254, 2021 | 106 | 2021 |
| Macrophage exclusion after radiation therapy (MERT): a first in human phase I/II trial using a CXCR4 inhibitor in glioblastoma RP Thomas, S Nagpal, M Iv, SG Soltys, S Bertrand, JS Pelpola, R Ball, ... Clinical Cancer Research 25 (23), 6948-6957, 2019 | 90 | 2019 |
| Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support I Banerjee, M Sofela, J Yang, JH Chen, NH Shah, R Ball, AI Mushlin, ... JAMA network open 2 (8), e198719-e198719, 2019 | 72 | 2019 |
| Predicting “heart age” using electrocardiography RL Ball, AH Feiveson, TT Schlegel, V Starc, AR Dabney Journal of personalized medicine 4 (1), 65-78, 2014 | 44 | 2014 |
| Predicting the lethal phenotype of the knockout mouse by integrating comprehensive genomic data Y Yuan, Y Xu, J Xu, RL Ball, H Liang Bioinformatics 28 (9), 1246-1252, 2012 | 44 | 2012 |
| Patient outcomes and cerebral infarction after ruptured anterior communicating artery aneurysm treatment JJ Heit, RL Ball, NA Telischak, HM Do, RL Dodd, GK Steinberg, ... American Journal of Neuroradiology 38 (11), 2119-2125, 2017 | 42 | 2017 |
| Evaluation of a smartphone decision-support tool for diarrheal disease management in a resource-limited setting F Haque, RL Ball, S Khatun, M Ahmed, S Kache, MJ Chisti, SA Sarker, ... PLoS neglected tropical diseases 11 (1), e0005290, 2017 | 41 | 2017 |
Matthew LungrenChief Scientific Officer Microsoft HLS, Adjunct Professor StanfordZweryfikowany adres z stanford.edu
