| Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study JR Zech, MA Badgeley, M Liu, AB Costa, JJ Titano, EK Oermann PLoS medicine 15 (11), e1002683, 2018 | 944 | 2018 |
| Automated deep-neural-network surveillance of cranial images for acute neurologic events JJ Titano, M Badgeley, J Schefflein, M Pain, A Su, M Cai, N Swinburne, ... Nature medicine 24 (9), 1337-1341, 2018 | 335 | 2018 |
| The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit YFY Chan, P Wang, L Rogers, N Tignor, M Zweig, SG Hershman, ... Nature biotechnology 35 (4), 354-362, 2017 | 181 | 2017 |
| Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams K Shameer, MA Badgeley, R Miotto, BS Glicksberg, JW Morgan, ... Briefings in bioinformatics 18 (1), 105-124, 2017 | 179 | 2017 |
| Deep learning predicts hip fracture using confounding patient and healthcare variables MA Badgeley, JR Zech, L Oakden-Rayner, BS Glicksberg, M Liu, W Gale, ... NPJ digital medicine 2 (1), 31, 2019 | 167 | 2019 |
| Natural language–based machine learning models for the annotation of clinical radiology reports J Zech, M Pain, J Titano, M Badgeley, J Schefflein, A Su, A Costa, ... Radiology 287 (2), 570-580, 2018 | 142 | 2018 |
| Deep learning guided stroke management: a review of clinical applications R Feng, M Badgeley, J Mocco, EK Oermann Journal of neurointerventional surgery 10 (4), 358-362, 2018 | 105 | 2018 |
| Hybrid nanoparticles improve targeting to inflammatory macrophages through phagocytic signals V Bagalkot, MA Badgeley, T Kampfrath, JA Deiuliis, S Rajagopalan, ... Journal of controlled release 217, 243-255, 2015 | 93 | 2015 |
| Confounding variables can degrade generalization performance of radiological deep learning models JR Zech, MA Badgeley, M Liu, AB Costa, JJ Titano, EK Oermann arXiv preprint arXiv:1807.00431, 2018 | 82 | 2018 |
| Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning K Shameer, BS Glicksberg, R Hodos, KW Johnson, MA Badgeley, ... Briefings in bioinformatics 19 (4), 656-678, 2018 | 78 | 2018 |
| EHDViz: clinical dashboard development using open-source technologies MA Badgeley, K Shameer, BS Glicksberg, MS Tomlinson, MA Levin, ... BMJ open 6 (3), e010579, 2016 | 72 | 2016 |
| Epidemiology of 10,000 high school football injuries: patterns of injury by position played MA Badgeley, NM McIlvain, EE Yard, SK Fields, RD Comstock Journal of physical activity and health 10 (2), 160-169, 2013 | 61 | 2013 |
| Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks BS Glicksberg, L Li, MA Badgeley, K Shameer, R Kosoy, ND Beckmann, ... Bioinformatics 32 (12), i101-i110, 2016 | 42 | 2016 |
| In vivo targeting of inflammation-associated myeloid-related protein 8/14 via gadolinium immunonanoparticles A Maiseyeu, MA Badgeley, T Kampfrath, G Mihai, JA Deiuliis, C Liu, ... Arteriosclerosis, thrombosis, and vascular biology 32 (4), 962-970, 2012 | 42 | 2012 |
| Bethany Percha, Thomas M Snyder, and Joel T Dudley MA Badgeley, JR Zech, L Oakden-Rayner, BS Glicksberg, M Liu, W Gale, ... Deep learning predicts hip fracture using confounding patient and healthcare …, 2019 | 29 | 2019 |
| PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model BS Glicksberg, B Oskotsky, PM Thangaraj, N Giangreco, MA Badgeley, ... Bioinformatics 35 (21), 4515-4518, 2019 | 27 | 2019 |
| Using deep-learning algorithms to simultaneously identify right and left ventricular dysfunction from the electrocardiogram A Vaid, KW Johnson, MA Badgeley, SS Somani, M Bicak, I Landi, ... Cardiovascular Imaging 15 (3), 395-410, 2022 | 26 | 2022 |
| Wide and deep volumetric residual networks for volumetric image classification V Arvind, A Costa, M Badgeley, S Cho, E Oermann arXiv preprint arXiv:1710.01217, 2017 | 19 | 2017 |
| Using deep learning to identify bladder cancers with FGFR‐activating mutations from histology images CS Velmahos, M Badgeley, YC Lo Cancer Medicine 10 (14), 4805-4813, 2021 | 18 | 2021 |
| Hybrid Bayesian-rank integration approach improves the predictive power of genomic dataset aggregation MA Badgeley, SC Sealfon, MD Chikina Bioinformatics 31 (2), 209-215, 2015 | 18 | 2015 |
