| SQuAD: 100,000+ Questions for Machine Comprehension of Text P Rajpurkar, J Zhang, K Lopyrev, P Liang Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 9507 | 2016 |
| CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning P Rajpurkar, J Irvin, K Zhu, B Yang, H Mehta, T Duan, D Ding, A Bagul, ... arXiv preprint arXiv:1711.05225, 2017 | 3724 | 2017 |
| Know What You Don't Know: Unanswerable Questions for SQuAD P Rajpurkar, R Jia, P Liang Proceedings of the 55th Annual Meeting of the Association for Computational …, 2018 | 3306 | 2018 |
| Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison J Irvin, P Rajpurkar, M Ko, Y Yu, S Ciurea-Ilcus, C Chute, H Marklund, ... Proceedings of the AAAI conference on artificial intelligence 33 (01), 590-597, 2019 | 3060 | 2019 |
| Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network AY Hannun, P Rajpurkar, M Haghpanahi, GH Tison, C Bourn, ... Nature medicine 25 (1), 65-69, 2019 | 2809 | 2019 |
| AI in health and medicine P Rajpurkar, E Chen, O Banerjee, EJ Topol Nature Medicine 28 (1), 31-38, 2022 | 1929 | 2022 |
| Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists P Rajpurkar, J Irvin, RL Ball, K Zhu, B Yang, H Mehta, T Duan, D Ding, ... PLOS Medicine 15 (11), e1002686, 2018 | 1331 | 2018 |
| Foundation models for generalist medical artificial intelligence M Moor, O Banerjee, ZSH Abad, HM Krumholz, J Leskovec, EJ Topol, ... Nature 616 (7956), 259-265, 2023 | 1104 | 2023 |
| Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks P Rajpurkar, AY Hannun, M Haghpanahi, C Bourn, AY Ng arXiv preprint arXiv:1707.01836, 2017 | 1020 | 2017 |
| An Empirical Evaluation of Deep Learning on Highway Driving B Huval, T Wang, S Tandon, J Kiske, W Song, J Pazhayampallil, ... arXiv preprint arXiv:1504.01716, 2015 | 990 | 2015 |
| Multimodal biomedical AI JN Acosta, GJ Falcone, P Rajpurkar, EJ Topol Nature Medicine 28 (9), 1773-1784, 2022 | 734 | 2022 |
| Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet N Bien, P Rajpurkar, RL Ball, J Irvin, A Park, E Jones, M Bereket, BN Patel, ... PLOS Medicine 15 (11), e1002699, 2018 | 714 | 2018 |
| MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs P Rajpurkar, J Irvin, A Bagul, D Ding, T Duan, H Mehta, B Yang, K Zhu, ... 1st Conference on Medical Imaging with Deep Learning, 2017 | 484* | 2017 |
| Self-supervised learning in medicine and healthcare R Krishnan, P Rajpurkar, EJ Topol Nature Biomedical Engineering 6 (12), 1346-1352, 2022 | 437 | 2022 |
| CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT A Smit, S Jain, P Rajpurkar, A Pareek, AY Ng, MP Lungren Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 342 | 2020 |
| Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning E Tiu, E Talius, P Patel, CP Langlotz, AY Ng, P Rajpurkar Nature Biomedical Engineering 6 (12), 1399-1406, 2022 | 307 | 2022 |
| The Current and Future State of AI Interpretation of Medical Images P Rajpurkar, MP Lungren New England Journal of Medicine 388 (21), 1981-1990, 2023 | 278 | 2023 |
| Impact of a deep learning assistant on the histopathologic classification of liver cancer A Kiani, B Uyumazturk, P Rajpurkar, A Wang, R Gao, E Jones, Y Yu, ... NPJ digital medicine 3 (1), 23, 2020 | 269 | 2020 |
| Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model A Park, C Chute, P Rajpurkar, J Lou, RL Ball, K Shpanskaya, ... JAMA Network Open 2 (6), e195600-e195600, 2019 | 258 | 2019 |
| Med-flamingo: a multimodal medical few-shot learner M Moor, Q Huang, S Wu, M Yasunaga, Y Dalmia, J Leskovec, C Zakka, ... Machine Learning for Health (ML4H), 353-367, 2023 | 243 | 2023 |
Andrew NgStanford UniversityE-mailová adresa ověřena na: cs.stanford.edu
