| 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 | 2301 | 2023 |
| Towards vqa models that can read A Singh, V Natarajan, M Shah, Y Jiang, X Chen, D Batra, D Parikh, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1071 | 2019 |
| Underspecification presents challenges for credibility in modern machine learning A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... Journal of Machine Learning Research 23 (226), 1-61, 2022 | 832 | 2022 |
| Toward expert-level medical question answering with large language models K Singhal, T Tu, J Gottweis, R Sayres, E Wulczyn, M Amin, L Hou, K Clark, ... Nature Medicine, 1-8, 2025 | 707 | 2025 |
| 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 | 699 | 2020 |
| Big self-supervised models advance medical image classification S Azizi, B Mustafa, F Ryan, Z Beaver, J Freyberg, J Deaton, A Loh, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 649 | 2021 |
| Towards generalist biomedical AI T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ... NEJM AI 1 (3), AIoa2300138, 2024 | 323 | 2024 |
| Contrastive training for improved out-of-distribution detection J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ... arXiv preprint arXiv:2007.05566, 2020 | 272 | 2020 |
| Pythia v0. 1: the winning entry to the vqa challenge 2018 Y Jiang, V Natarajan, X Chen, M Rohrbach, D Batra, D Parikh arXiv preprint arXiv:1807.09956, 2018 | 238 | 2018 |
| 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 | 159 | 2023 |
| Pythia-A platform for vision & language research A Singh, V Natarajan, Y Jiang, X Chen, M Shah, M Rohrbach, D Batra, ... | 157* | 2018 |
| Towards conversational diagnostic ai T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ... arXiv preprint arXiv:2401.05654, 2024 | 150 | 2024 |
| Capabilities of gemini models in medicine K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ... arXiv preprint arXiv:2404.18416, 2024 | 132 | 2024 |
| Dermgan: Synthetic generation of clinical skin images with pathology A Ghorbani, V Natarajan, D Coz, Y Liu Machine learning for health workshop, 155-170, 2020 | 128 | 2020 |
| Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ... Medical Image Analysis 75, 102274, 2022 | 124 | 2022 |
| Medperf: open benchmarking platform for medical artificial intelligence using federated evaluation A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, S Bala, ... arXiv preprint arXiv:2110.01406, 2021 | 116* | 2021 |
| Maintaining fairness across distribution shift: do we have viable solutions for real-world applications J Schrouff, N Harris, O Koyejo, I Alabdulmohsin, E Schnider, ... arXiv preprint arXiv:2202.01034, 2022 | 103* | 2022 |
| 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 | 86 | 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 | 78 | 2022 |
| Building Customized User Profiles Based on Conversational Data V Natarajan, W Yang, LIU Honglei, A Kumar US Patent App. 15/967,239, 2019 | 74 | 2019 |
Alan KarthikesalingamGoogle HealthVerified email at google.com