| International evaluation of an AI system for breast cancer screening SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ... Nature 577 (7788), 89-94, 2020 | 2208 | 2020 |
| Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 720 | 2023 |
| Capabilities of gpt-4 on medical challenge problems H Nori, N King, SM McKinney, D Carignan, E Horvitz arXiv preprint arXiv:2303.13375, 2023 | 431 | 2023 |
| Spontaneous brain rhythms predict sleep stability in the face of noise TT Dang-Vu, SM McKinney, OM Buxton, JM Solet, JM Ellenbogen Current biology 20 (15), R626-R627, 2010 | 348 | 2010 |
| Chest radiograph interpretation with deep learning models: assessment with radiologist-adjudicated reference standards and population-adjusted evaluation A Majkowska, S Mittal, DF Steiner, JJ Reicher, SM McKinney, GE Duggan, ... Radiology 294 (2), 421-431, 2020 | 248 | 2020 |
| Sleep disruption due to hospital noises: a prospective evaluation OM Buxton, JM Ellenbogen, W Wang, A Carballeira, S O'Connor, ... Annals of internal medicine 157 (3), 170-179, 2012 | 210 | 2012 |
| The subjective–objective mismatch in sleep perception among those with insomnia and sleep apnea MT Bianchi, KL Williams, S Mckinney, JM Ellenbogen Journal of sleep research 22 (5), 557-568, 2013 | 176 | 2013 |
| Covert waking brain activity reveals instantaneous sleep depth SM McKinney, TT Dang-Vu, OM Buxton, JM Solet, JM Ellenbogen PloS one 6 (3), e17351, 2011 | 86 | 2011 |
| Supervised transfer learning at scale for medical imaging B Mustafa, A Loh, J Freyberg, P MacWilliams, M Wilson, SM McKinney, ... arXiv preprint arXiv:2101.05913, 2021 | 69 | 2021 |
| Robust and efficient medical imaging with self-supervision S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... arXiv preprint arXiv:2205.09723, 2022 | 52 | 2022 |
| Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... Nature Biomedical Engineering 7 (6), 756-779, 2023 | 51 | 2023 |
| Can generalist foundation models outcompete special-purpose tuning? case study in medicine H Nori, YT Lee, S Zhang, D Carignan, R Edgar, N Fusi, N King, J Larson, ... arXiv preprint arXiv:2311.16452, 2023 | 48 | 2023 |
| DiBa: a data-driven Bayesian algorithm for sleep spindle detection B Babadi, SM McKinney, V Tarokh, JM Ellenbogen IEEE Transactions on Biomedical Engineering 59 (2), 483-493, 2011 | 48 | 2011 |
| Insights into puberty: the relationship between sleep stages and pulsatile LH secretion ND Shaw, JP Butler, SM McKinney, SA Nelson, JM Ellenbogen, JE Hall The Journal of Clinical Endocrinology & Metabolism 97 (11), E2055-E2062, 2012 | 44 | 2012 |
| Deep learning detection of active pulmonary tuberculosis at chest radiography matched the clinical performance of radiologists S Kazemzadeh, J Yu, S Jamshy, R Pilgrim, Z Nabulsi, C Chen, N Beladia, ... Radiology 306 (1), 124-137, 2023 | 24 | 2023 |
| Deep learning to detect OCT-derived diabetic macular edema from color retinal photographs: a multicenter validation study X Liu, TK Ali, P Singh, A Shah, SM McKinney, P Ruamviboonsuk, ... Ophthalmology Retina 6 (5), 398-410, 2022 | 22 | 2022 |
| Reply to: Transparency and reproducibility in artificial intelligence SM McKinney, A Karthikesalingam, D Tse, CJ Kelly, Y Liu, GS Corrado, ... Nature 586 (7829), E17-E18, 2020 | 20 | 2020 |
| Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians K Dvijotham, J Winkens, M Barsbey, S Ghaisas, R Stanforth, N Pawlowski, ... Nature Medicine 29 (7), 1814-1820, 2023 | 19 | 2023 |
| A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment RG Gomes, B Vwalika, C Lee, A Willis, M Sieniek, JT Price, C Chen, ... Communications Medicine 2 (1), 128, 2022 | 13 | 2022 |
| Automated extraction of structured labels from medical text using deep convolutional networks and use thereof to train a computer vision model S McKinney, S Shetty, H Mostofi US Patent App. 16/958,544, 2021 | 11 | 2021 |
