| 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 | 717 | 2022 |
| 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 | 185 | 2020 |
| Predicting the risk of developing diabetic retinopathy using deep learning A Bora, S Balasubramanian, B Babenko, S Virmani, S Venugopalan, ... The Lancet Digital Health 3 (1), e10-e19, 2021 | 173 | 2021 |
| Disengagement of motor cortex from movement control during long-term learning EJ Hwang, JE Dahlen, YY Hu, K Aguilar, B Yu, M Mukundan, A Mitani, ... Science advances 5 (10), eaay0001, 2019 | 92 | 2019 |
| Detection of signs of disease in external photographs of the eyes via deep learning B Babenko, A Mitani, I Traynis, N Kitade, P Singh, AY Maa, J Cuadros, ... Nature biomedical engineering 6 (12), 1370-1383, 2022 | 56 | 2022 |
| Real-time processing of two-photon calcium imaging data including lateral motion artifact correction A Mitani, T Komiyama Frontiers in neuroinformatics 12, 98, 2018 | 48 | 2018 |
| Brain-computer interface with inhibitory neurons reveals subtype-specific strategies A Mitani, M Dong, T Komiyama Current Biology 28 (1), 77-83. e4, 2018 | 33 | 2018 |
| Artificial intelligence predictive model for hormone therapy use in prostate cancer DE Spratt, S Tang, Y Sun, HC Huang, E Chen, O Mohamad, AJ Armstrong, ... NEJM evidence 2 (8), EVIDoa2300023, 2023 | 28 | 2023 |
| Whisker row deprivation affects the flow of sensory information through rat barrel cortex V Jacob, A Mitani, T Toyoizumi, K Fox Journal of Neurophysiology 117 (1), 4-17, 2017 | 18 | 2017 |
| Underspecification presents challenges for credibility in modern machine learning, 2020 A D’Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... arXiv preprint arXiv:2011.03395, 2011 | 15 | 2011 |
| Underspecification presents challenges for credibility in modern machine learning. arXiv A D’Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... arXiv preprint arXiv:2011.03395, 2020 | 11 | 2020 |
| A leaky-integrator model as a control mechanism underlying flexible decision making during task switching A Mitani, R Sasaki, M Oizumi, T Uka PloS one 8 (3), e59670, 2013 | 9 | 2013 |
| Improving medical annotation quality to decrease labeling burden using stratified noisy cross-validation J Hsu, S Phene, A Mitani, J Luo, N Hammel, J Krause, R Sayres arXiv preprint arXiv:2009.10858, 2020 | 6 | 2020 |
| Disengagement of motor cortex from movement control during long-term learning. Sci Adv 5: eaay0001 EJ Hwang, JE Dahlen, YY Hu, K Aguilar, B Yu, M Mukundan, A Mitani, ... | 6 | 2019 |
| Improved multimodal fusion for small datasets with auxiliary supervision G Holste, D van der Wal, H Pinckaers, R Yamashita, A Mitani, A Esteva 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5, 2023 | 5 | 2023 |
| Retinal detection of kidney disease and diabetes A Mitani, N Hammel, Y Liu Nature biomedical engineering 5 (6), 487-489, 2021 | 4 | 2021 |
| Detecting hidden signs of diabetes in external eye photographs B Babenko, A Mitani, I Traynis, N Kitade, P Singh, A Maa, J Cuadros, ... arXiv preprint arXiv:2011.11732, 2020 | 4 | 2020 |
| Machine Learning for Detection of Diseases from External Anterior Eye Images Y Liu, N Hammel, A Mitani, DJ Wu, AD Bora, AV Varadarajan, ... US Patent App. 18/011,597, 2023 | 2 | 2023 |
| Digital histopathology-based multimodal artificial intelligence scores predict risk of progression in a randomized phase III trial in patients with nonmetastatic castration … FY Feng, MR Smith, F Saad, P Mobadersany, SK Tian, SSF Yip, ... Journal of Clinical Oncology 41 (16_suppl), 5035-5035, 2023 | 2 | 2023 |
| Task-specific employment of sensory signals underlies rapid task switching R Sasaki, H Kumano, A Mitani, Y Suda, T Uka Cerebral Cortex 32 (21), 4657-4670, 2022 | 2 | 2022 |
