Articoli con mandati relativi all'accesso pubblico - Greg CorradoUlteriori informazioni
Non disponibili pubblicamente: 3
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
Mandati: Cancer Research UK
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
Mandati: US National Institutes of Health
Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities
S Kazemzadeh, AP Kiraly, Z Nabulsi, N Sanjase, M Maimbolwa, B Shuma, ...
NEJM AI 1 (10), AIoa2400018, 2024
Mandati: Bill & Melinda Gates Foundation
Disponibili pubblicamente: 19
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
Mandati: Cancer Research UK, National Institute for Health Research, UK
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
D Ardila, AP Kiraly, S Bharadwaj, B Choi, JJ Reicher, L Peng, D Tse, ...
Nature medicine 25 (6), 954-961, 2019
Mandati: US National Institutes of Health
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
R Poplin, AV Varadarajan, K Blumer, Y Liu, MV McConnell, GS Corrado, ...
Nature biomedical engineering 2 (3), 158-164, 2018
Mandati: UK Medical Research Council
Stimulus onset quenches neural variability: a widespread cortical phenomenon
MM Churchland, BM Yu, JP Cunningham, LP Sugrue, MR Cohen, ...
Nature neuroscience 13 (3), 369-378, 2010
Mandati: US National Institutes of Health, Howard Hughes Medical Institute
Ensuring fairness in machine learning to advance health equity
A Rajkomar, M Hardt, MD Howell, G Corrado, MH Chin
Annals of internal medicine 169 (12), 866-872, 2018
Mandati: US National Institutes of Health
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ...
Nature medicine 28 (1), 154-163, 2022
Mandati: Academy of Finland, Netherlands Organisation for Scientific Research …
Detection of anaemia from retinal fundus images via deep learning
A Mitani, A Huang, S Venugopalan, GS Corrado, L Peng, DR Webster, ...
Nature biomedical engineering 4 (1), 18-27, 2020
Mandati: UK Medical Research Council
Deep learning for predicting refractive error from retinal fundus images
AV Varadarajan, R Poplin, K Blumer, C Angermueller, J Ledsam, ...
Investigative ophthalmology & visual science 59 (7), 2861-2868, 2018
Mandati: UK Medical Research Council, National Institute for Health Research, UK
Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs
S Phene, RC Dunn, N Hammel, Y Liu, J Krause, N Kitade, ...
Ophthalmology 126 (12), 1627-1639, 2019
Mandati: US National Institutes of Health
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
AV Varadarajan, P Bavishi, P Ruamviboonsuk, P Chotcomwongse, ...
Nature communications 11 (1), 130, 2020
Mandati: National Institute for Health Research, UK
Determining breast cancer biomarker status and associated morphological features using deep learning
P Gamble, R Jaroensri, H Wang, F Tan, M Moran, T Brown, ...
Communications medicine 1 (1), 14, 2021
Mandati: US Department of Defense
Deviation from the matching law reflects an optimal strategy involving learning over multiple timescales
K Iigaya, Y Ahmadian, LP Sugrue, GS Corrado, Y Loewenstein, ...
Nature communications 10 (1), 1466, 2019
Mandati: US National Science Foundation, US National Institutes of Health, Howard …
Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: Insights from spring 2020
LR Woskie, J Hennessy, V Espinosa, TC Tsai, S Vispute, BH Jacobson, ...
Plos one 16 (6), e0253071, 2021
Mandati: European Commission
Deep learning models for histologic grading of breast cancer and association with disease prognosis
R Jaroensri, E Wulczyn, N Hegde, T Brown, I Flament-Auvigne, F Tan, ...
NPJ Breast cancer 8 (1), 113, 2022
Mandati: US Department of Defense
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
Mandati: UK Medical Research Council, National Institute for Health Research, UK
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
Mandati: Bill & Melinda Gates Foundation
A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study
B Babenko, I Traynis, C Chen, P Singh, A Uddin, J Cuadros, LP Daskivich, ...
The Lancet Digital Health 5 (5), e257-e264, 2023
Mandati: US National Institutes of Health, US Department of Veterans Affairs
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