| How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals E Wu, K Wu, R Daneshjou, D Ouyang, DE Ho, J Zou Nature Medicine 27 (4), 582-584, 2021 | 385 | 2021 |
| Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach W Lotter, AR Diab, B Haslam, JG Kim, G Grisot, E Wu, K Wu, JO Onieva, ... Nature medicine 27 (2), 244-249, 2021 | 383 | 2021 |
| GPT detectors are biased against non-native English writers W Liang, M Yuksekgonul, Y Mao, E Wu, J Zou Patterns 4 (7), 2023 | 354 | 2023 |
| From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou Cell 186 (8), 1772-1791, 2023 | 242 | 2023 |
| Conditional infilling GANs for data augmentation in mammogram classification E Wu, K Wu, D Cox, W Lotter MICCAI 2018, Breast Image Analysis Workshop, 98-106, 2018 | 199 | 2018 |
| Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens Z Wu, AE Trevino, E Wu, K Swanson, HJ Kim, HB D’Angio, R Preska, ... Nature Biomedical Engineering 6 (12), 1435-1448, 2022 | 90 | 2022 |
| ClashEval: Quantifying the tug-of-war between an LLM’s internal prior and external evidence K Wu, E Wu, J Zou arXiv preprint arXiv:2404.10198, 2024 | 55* | 2024 |
| Datainf: Efficiently estimating data influence in lora-tuned llms and diffusion models Y Kwon, E Wu, K Wu, J Zou arXiv preprint arXiv:2310.00902, 2023 | 47 | 2023 |
| Characterizing the clinical adoption of medical AI devices through US insurance claims K Wu, E Wu, B Theodorou, W Liang, C Mack, L Glass, J Sun, J Zou NEJM AI 1 (1), AIoa2300030, 2024 | 45 | 2024 |
| How well do LLMs cite relevant medical references? An evaluation framework and analyses K Wu, E Wu, A Cassasola, A Zhang, K Wei, T Nguyen, S Riantawan, ... arXiv preprint arXiv:2402.02008, 2024 | 34 | 2024 |
| Learning scene gist with convolutional neural networks to improve object recognition K Wu, E Wu, G Kreiman 2018 52nd Annual Conference on Information Sciences and Systems (CISS), 1-6, 2018 | 31 | 2018 |
| Leveraging physiology and artificial intelligence to deliver advancements in health care A Zhang, Z Wu, E Wu, M Wu, MP Snyder, J Zou, JC Wu Physiological Reviews 103 (4), 2423-2450, 2023 | 26 | 2023 |
| Synthesizing lesions using contextual GANs improves breast cancer classification on mammograms E Wu, K Wu, W Lotter arXiv preprint arXiv:2006.00086, 2020 | 26 | 2020 |
| 7-UP: Generating in silico CODEX from a small set of immunofluorescence markers E Wu, AE Trevino, Z Wu, K Swanson, HJ Kim, HB D’Angio, R Preska, ... PNAS nexus 2 (6), pgad171, 2023 | 18 | 2023 |
| Machine learning prediction of clinical trial operational efficiency K Wu, E Wu, M DAndrea, N Chitale, M Lim, M Dabrowski, K Kantor, ... The AAPS Journal 24 (3), 57, 2022 | 15 | 2022 |
| Validation of a deep learning mammography model in a population with low screening rates K Wu, E Wu, Y Wu, H Tan, G Sorensen, M Wang, B Lotter NeurIPS 2019, Fair ML for Health Workshop, 2019 | 9 | 2019 |
| Discovery and generalization of tissue structures from spatial omics data Z Wu, A Kondo, M McGrady, EAG Baker, B Chidester, E Wu, MK Rahim, ... Cell Reports Methods 4 (8), 2024 | 3 | 2024 |
| Regulating AI Adaptation: An Analysis of AI Medical Device Updates K Wu, E Wu, K Rodolfa, DE Ho, J Zou medRxiv, 2024.06. 26.24309506, 2024 | 3 | 2024 |
| Explaining medical AI performance disparities across sites with confounder Shapley value analysis E Wu, K Wu, J Zou NeurIPS, Machine Learning for Health Workshop 2021, 2021 | 3 | 2021 |
| The literacy barrier in clinical trial consents: a retrospective analysis FN Mirza, E Wu, HF Abdulrazeq, ID Connolly, OY Tang, CK Zogg, ... EClinicalMedicine 75, 2024 | 1 | 2024 |
Kevin Y WuGraduate Student, Stanford UniversityBestätigte E-Mail-Adresse bei stanford.edu