| Dermatologist-level classification of skin cancer with deep neural networks A Esteva, B Kuprel, RA Novoa, J Ko, SM Swetter, HM Blau, S Thrun nature 542 (7639), 115-118, 2017 | 13033 | 2017 |
| A guide to deep learning in healthcare A Esteva, A Robicquet, B Ramsundar, V Kuleshov, M DePristo, K Chou, ... Nature medicine 25 (1), 24-29, 2019 | 3250 | 2019 |
| 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 4 (1), 1-9, 2021 | 916 | 2021 |
| Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ... The Lancet Digital Health 2 (10), e537-e548, 2020 | 846 | 2020 |
| Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ... The Lancet Digital Health 2 (10), e549-e560, 2020 | 699 | 2020 |
| In silico labeling: predicting fluorescent labels in unlabeled images EM Christiansen, SJ Yang, DM Ando, A Javaherian, G Skibinski, S Lipnick, ... Cell 173 (3), 792-803. e19, 2018 | 623 | 2018 |
| Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... bmj 377, 2022 | 333 | 2022 |
| Correction: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks A Esteva, B Kuprel, RA Novoa, J Ko, SM Swetter, HM Blau, S Thrun Nature 546 (7660), 686-686, 2017 | 237 | 2017 |
| Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains N Naik, A Madani, A Esteva, NS Keskar, MF Press, D Ruderman, DB Agus, ... Nature communications 11 (1), 5727, 2020 | 206 | 2020 |
| COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization A Esteva, A Kale, R Paulus, K Hashimoto, W Yin, D Radev, R Socher NPJ digital medicine 4 (1), 68, 2021 | 163 | 2021 |
| A mountable toilet system for personalized health monitoring via the analysis of excreta S Park, DD Won, BJ Lee, D Escobedo, A Esteva, A Aalipour, TJ Ge, ... Nature biomedical engineering 4 (6), 624-635, 2020 | 149 | 2020 |
| Health information management: implications of artificial intelligence on healthcare data and information management MH Stanfill, DT Marc Yearbook of medical informatics 28 (01), 056-064, 2019 | 134 | 2019 |
| Two distinct scene-processing networks connecting vision and memory C Baldassano, A Esteva, L Fei-Fei, DM Beck Eneuro 3 (5), 2016 | 129 | 2016 |
| A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI V Sounderajah, H Ashrafian, S Rose, NH Shah, M Ghassemi, R Golub, ... Nature medicine 27 (10), 1663-1665, 2021 | 112 | 2021 |
| Visual scenes are categorized by function. MR Greene, C Baldassano, A Esteva, DM Beck, L Fei-Fei Journal of Experimental Psychology: General 145 (1), 82, 2016 | 103 | 2016 |
| Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials A Esteva, J Feng, D van der Wal, SC Huang, JP Simko, S DeVries, ... NPJ digital medicine 5 (1), 71, 2022 | 74 | 2022 |
| Deep networks for early stage skin disease and skin cancer classification A Esteva, B Kuprel, S Thrun Project Report, Stanford University, 2015 | 62 | 2015 |
| Melanoma early detection: big data, bigger picture T Petrie, R Samatham, AM Witkowski, A Esteva, SA Leachman Journal of Investigative Dermatology 139 (1), 25-30, 2019 | 61 | 2019 |
| Skin cancer detection and tracking using data synthesis and deep learning Y Li, A Esteva, B Kuprel, R Novoa, J Ko, S Thrun Workshops at the thirty-first AAAI conference on artificial intelligence, 2017 | 46 | 2017 |
| Vision-based classification of developmental disorders using eye-movements G Pusiol, A Esteva, SS Hall, M Frank, A Milstein, L Fei-Fei Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 45 | 2016 |
Justin KoProfessor of Dermatology, Stanford University School of MedicineVerified email at stanford.edu
