Ng, Andrew Y.

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

Hannun, A. Y., Rajpurkar, P., Haghpanahi, M., Tison, G. H., Bourn, C., Turakhia, M. P., & Ng, A. Y. (2019) · Nature Medicine

ECG Monitoring and AnalysisCardiac electrophysiology and arrhythmias

Cited by 3,148

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

Lee, H., Grosse, R., Ranganath, R., & Ng, A. Y. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 2,412

Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks

Snow, R., O'Connor, B., Jurafsky, D., & Ng, A. Y. (2008) · Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08

Natural Language Processing TechniquesMobile Crowdsensing and Crowdsourcing

Cited by 1,887

Feature selection, L 1 vs. L 2 regularization, and rotational invariance

Ng, A. Y. (2004) · Twenty-first international conference on Machine learning - ICML '04

Statistical Methods and InferenceMachine Learning and Algorithms

Cited by 1,572

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

Rajpurkar, P., Irvin, J., Ball, R. L., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D., Bagul, A., Langlotz, C. P., et al. (2018) · PLOS Medicine

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 1,449

Large-scale deep unsupervised learning using graphics processors

Raina, R., Madhavan, A., & Ng, A. Y. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning

Parallel Computing and Optimization TechniquesNeural Networks and Applications

Cited by 742

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

Bien, N., Rajpurkar, P., Ball, R. L., Irvin, J., Park, A., Jones, E., Bereket, M., Patel, B. N., Yeom, K. W., Shpanskaya, K., et al. (2018) · PLOS Medicine

Artificial Intelligence in Healthcare and EducationMedical Imaging and Analysis

Cited by 734

End-to-End People Detection in Crowded Scenes

Stewart, R., Andriluka, M., & Ng, A. Y. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 539

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning

Tiu, E., Talius, E., Patel, P., Langlotz, C. P., Ng, A. Y., & Rajpurkar, P. (2022) · Nature Biomedical Engineering

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 442

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al. (2019) · arXiv

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 392

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 392

Tackling climate change with machine learning

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys

Climate Change and Environmental ImpactArtificial Intelligence Applications

Cited by 336

Impact of a deep learning assistant on the histopathologic classification of liver cancer

Kiani, A., Uyumazturk, B., Rajpurkar, P., Wang, A., Gao, R., Jones, E., Yu, Y., Langlotz, C. P., Ball, R. L., Montine, T. J., et al. (2020) · npj Digital Medicine

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 325

Benchmarking saliency methods for chest X-ray interpretation

Saporta, A., Gui, X., Agrawal, A., Pareek, A., Truong, S. Q. H., Nguyen, C. D. T., Ngo, V.-D., Seekins, J., Blankenberg, F. G., Ng, A. Y., et al. (2022) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)COVID-19 diagnosis using AI

Cited by 270

Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model

Park, A., Chute, C., Rajpurkar, P., Lou, J., Ball, R. L., Shpanskaya, K., Jabarkheel, R., Kim, L. H., McKenna, E., Tseng, J., et al. (2019) · JAMA Network Open

Intracranial Aneurysms: Treatment and ComplicationsMedical Image Segmentation Techniques

Cited by 258

Evaluating progress in automatic chest X-ray radiology report generation

Yu, F., Endo, M., Krishnan, R., Pan, I., Tsai, A., Reis, E. P., Fonseca, E. K. U. N., Lee, H. M. H., Abad, Z. S. H., Ng, A. Y., et al. (2023) · Patterns

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 200

CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV

Rajpurkar, P., O’Connell, C., Schechter, A., Asnani, N., Li, J., Kiani, A., Ball, R. L., Mendelson, M., Maartens, G., van Hoving, D. J., et al. (2020) · npj Digital Medicine

COVID-19 diagnosis using AITuberculosis Research and Epidemiology

Cited by 137

MedAgentBench: a virtual EHR environment to benchmark medical LLM agents

Jiang, Y., Black, K. C., Geng, G., Park, D., Zou, J., Ng, A. Y., & Chen, J. H. (2025) · NEJM AI

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 66

Development and Validation of an Artificial Intelligence System to Optimize Clinician Review of Patient Records

Chi, E. A., Chi, G., Tsui, C. T., Jiang, Y., Jarr, K., Kulkarni, C. V., Zhang, M., Long, J., Ng, A. Y., Rajpurkar, P., et al. (2021) · JAMA Network Open

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 64

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Jain, S., Agrawal, A., Saporta, A., Truong, S. Q., Nguyen Duong, D., Bui, T., Chambon, P., Lungren, M., Ng, A., Langlotz, C., et al. (2021) · PhysioNet

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 34

SmartAlert: Integrating Machine Learning and Alert Triggers into Live Electronic Medical Record Systems, Targeting Low-Yield Inpatient Lab Tests

Jiang, Y., Ma, S. P., Liang, A. S., Kim, G., Acharya, A., Mony, S., Punnathanam, S., Makeown, J., Jose, J., Shieh, L., et al. (2026) · medRxiv

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 1