| 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, 2018 | 1165 | 2018 |
| Detecting cancer metastases on gigapixel pathology images Y Liu, K Gadepalli, M Norouzi, GE Dahl, T Kohlberger, A Boyko, ... arXiv preprint arXiv:1703.02442, 2017 | 663 | 2017 |
| Deep learning-enabled medical computer vision A Esteva, K Chou, S Yeung, N Naik, A Madani, A Mottaghi, Y Liu, E Topol, ... npj Digital Medicine, 2021 | 324 | 2021 |
| Impact of deep learning assistance on the histopathologic review of lymph nodes for metastatic breast cancer DF Steiner, R MacDonald, Y Liu, P Truszkowski, JD Hipp, C Gammage, ... The American journal of surgical pathology 42 (12), 1636, 2018 | 319 | 2018 |
| Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer K Nagpal, D Foote, Y Liu, PHC Chen, E Wulczyn, F Tan, N Olson, ... NPJ digital medicine 2 (1), 48, 2019 | 316 | 2019 |
| How to read articles that use machine learning: Users’ Guides to the Medical Literature Y Liu, PHC Chen, J Krause, L Peng Jama 322 (18), 1806-1816, 2019 | 296 | 2019 |
| 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, 2020 | 293 | 2020 |
| Artificial intelligence–based breast cancer nodal metastasis detection: Insights into the black box for pathologists Y Liu, T Kohlberger, M Norouzi, GE Dahl, JL Smith, A Mohtashamian, ... Archives of pathology & laboratory medicine 143 (7), 859-868, 2019 | 259 | 2019 |
| An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis MCS Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, Yun Liu ... Nature Medicine, 2019 | 196* | 2019 |
| Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation A Majkowska, S Mittal, DF Steiner, JJ Reicher, SM McKinney, GE Duggan, ... Radiology, 2019 | 169 | 2019 |
| How to develop machine learning models for healthcare PHC Chen*, Y Liu*, L Peng Nature Materials 18 (5), 410, 2019 | 168 | 2019 |
| Deep learning-based survival prediction for multiple cancer types using histopathology images E Wulczyn, DF Steiner, Z Xu, A Sadhwani, H Wang, I Flament-Auvigne, ... PLOS ONE, 2020 | 141 | 2020 |
| 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 | 121 | 2019 |
| Charting the Landscape of Tandem BRCT Domain-Mediated Protein Interactions NT Woods, RD Mesquita, M Sweet, MA Carvalho, X Li, Y Liu, H Nguyen, ... Science Signalling 5 (242), rs6, 2012 | 110 | 2012 |
| 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, 2019 | 108 | 2019 |
| Similar image search for histopathology: SMILY MCS Narayan Hegde, Jason D Hipp, Yun Liu, Michael E Buck, Emily Reif, Daniel ... npj Digital Medicine 2 (1), 56, 2019 | 86* | 2019 |
| Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens K Nagpal, D Foote, F Tan, Y Liu, PHC Chen, DF Steiner, N Manoj, ... JAMA Oncology, 2020 | 84 | 2020 |
| LS-SNP/PDB: annotated non-synonymous SNPs mapped to Protein Data Bank structures M Ryan, M Diekhans, S Lien, Y Liu, R Karchin Bioinformatics 25 (11), 1431-1432, 2009 | 81 | 2009 |
| Predicting the risk of developing diabetic retinopathy using deep learning A Bora, S Balasubramanian, B Babenko, S Virmani, S Venugopalan, ... The Lancet Digital Health, 2020 | 71 | 2020 |
| Interpretable survival prediction for colorectal cancer using deep learning E Wulczyn, DF Steiner, M Moran, M Plass, R Reihs, F Tan, ... npj Digital Medicine, 2021 | 55 | 2021 |
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