| Predicting conversion to wet age-related macular degeneration using deep learning J Yim, R Chopra, T Spitz, J Winkens, A Obika, C Kelly, H Askham, M Lukic, ... Nature Medicine 26 (6), 892-899, 2020 | 275 | 2020 |
| Quantitative analysis of OCT for neovascular age-related macular degeneration using deep learning G Moraes, DJ Fu, M Wilson, H Khalid, SK Wagner, E Korot, D Ferraz, ... Ophthalmology 128 (5), 693-705, 2021 | 110 | 2021 |
| 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 | 67 | 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 | 22 | 2022 |
| Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study M Schaekermann, T Spitz, M Pyles, H Cole-Lewis, E Wulczyn, SR Pfohl, ... EClinicalMedicine 70, 2024 | 6 | 2024 |
| AI system for fetal ultrasound in low-resource settings RG Gomes, B Vwalika, C Lee, A Willis, M Sieniek, JT Price, C Chen, ... arXiv preprint arXiv:2203.10139, 2022 | 5 | 2022 |
| Predicting disease progression from tissue images and tissue segmentation maps J Yim, RK Chopra, T Spitz, JH Winkens, AAN Obika, T Back, JR Ledsam, ... US Patent 11,935,232, 2024 | 2 | 2024 |
| Google and DeepMind: Deep Learning Systems in Ophthalmology X Liu, A Mitani, T Spitz, DJ Wu, JR Ledsam Artificial Intelligence in Ophthalmology, 161-176, 2021 | 2 | 2021 |
| Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings RV Rikhye, A Loh, GE Hong, P Singh, MA Smith, V Muralidharan, D Wong, ... arXiv preprint arXiv:2402.15566, 2024 | 1 | 2024 |
| Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians (CoDoC) K Dvijotham, J Winkens, M Barsbey, S Ghaisas, N Pawlowski, R Stanforth, ... | 1 | 2022 |
| Quantitative analysis of change in retinal tissues in neovascular age-related macular degeneration using artificial intelligence R Chopra, G Moraes, DJ Fu, S Wagner, T Spitz, M Wilson, J Yim, ... Investigative Ophthalmology & Visual Science 61 (7), 1152-1152, 2020 | 1 | 2020 |
| MINT: A wrapper to make multi-modal and multi-image AI models interactive J Freyberg, AG Roy, T Spitz, B Freeman, M Schaekermann, P Strachan, ... arXiv preprint arXiv:2401.12032, 2024 | | 2024 |
| Automatic segmentation using artificial intelligence of baseline anatomical parameters of patients starting anti-VEGF injections for neovascular age-related macular degeneration G Moraes, R Chopra, DJ Fu, S Wagner, T Spitz, M Wilson, J Yim, ... Investigative Ophthalmology & Visual Science 61 (7), 1633-1633, 2020 | | 2020 |
