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| Direct detection of DNA methylation during single-molecule, real-time sequencing BA Flusberg, DR Webster, JH Lee, KJ Travers, EC Olivares, TA Clark, ... Nature methods 7 (6), 461-465, 2010 | 1688 | 2010 |
| Large language models encode clinical knowledge K Singhal, S Azizi, T Tu, SS Mahdavi, J Wei, HW Chung, N Scales, ... Nature 620 (7972), 172-180, 2023 | 1680 | 2023 |
| 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 | 1657 | 2018 |
| Origins of the E. coli strain causing an outbreak of hemolytic–uremic syndrome in Germany DA Rasko, DR Webster, JW Sahl, A Bashir, N Boisen, F Scheutz, ... New England Journal of Medicine 365 (8), 709-717, 2011 | 1083 | 2011 |
| The origin of the Haitian cholera outbreak strain CS Chin, J Sorenson, JB Harris, WP Robins, RC Charles, ... New England Journal of Medicine 364 (1), 33-42, 2011 | 924 | 2011 |
| A deep learning system for differential diagnosis of skin diseases Y Liu, A Jain, C Eng, DH Way, K Lee, P Bui, K Kanada, ... Nature medicine 26 (6), 900-908, 2020 | 613 | 2020 |
| Massively multitask networks for drug discovery B Ramsundar, S Kearnes, P Riley, D Webster, D Konerding, V Pande arXiv preprint arXiv:1502.02072, 2015 | 606 | 2015 |
| Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy J Krause, V Gulshan, E Rahimy, P Karth, K Widner, GS Corrado, L Peng, ... Ophthalmology 125 (8), 1264-1272, 2018 | 520 | 2018 |
| Towards expert-level medical question answering with large language models K Singhal, T Tu, J Gottweis, R Sayres, E Wulczyn, L Hou, K Clark, S Pfohl, ... arXiv preprint arXiv:2305.09617, 2023 | 484 | 2023 |
| Deep learning in ophthalmology: the technical and clinical considerations DSW Ting, L Peng, AV Varadarajan, PA Keane, PM Burlina, MF Chiang, ... Progress in retinal and eye research 72, 100759, 2019 | 450 | 2019 |
| Using a deep learning algorithm and integrated gradients explanation to assist grading for diabetic retinopathy R Sayres, A Taly, E Rahimy, K Blumer, D Coz, N Hammel, J Krause, ... Ophthalmology 126 (4), 552-564, 2019 | 406 | 2019 |
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| Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program P Ruamviboonsuk, J Krause, P Chotcomwongse, R Sayres, R Raman, ... NPJ digital medicine 2 (1), 25, 2019 | 222 | 2019 |
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| Classification of nucleic acid templates B Flusberg, S Turner, J Lee, L Jia, J Korlach, J Sorenson, D Webster, ... US Patent App. 13/930,178, 2013 | 202* | 2013 |
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