Natarajan, Vivek

Big Self-Supervised Models Advance Medical Image Classification

Azizi, S., Mustafa, B., Ryan, F., Beaver, Z., Freyberg, J., Deaton, J., Loh, A., Karthikesalingam, A., Kornblith, S., Chen, T., et al. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

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Underspecification Presents Challenges for Credibility in Modern Machine Learning

D'Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., et al. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

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Federated benchmarking of medical artificial intelligence with MedPerf

Karargyris, A., Umeton, R., Sheller, M. J., Aristizabal, A., George, J., Wuest, A., Pati, S., Kassem, H., Zenk, M., Baid, U., et al. (2023) · Nature Machine Intelligence

Artificial Intelligence in Healthcare and EducationPrivacy-Preserving Technologies in Data

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Does your dermatology classifier know what it doesn’t know? Detecting the long-tail of unseen conditions

Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., et al. (2022) · Medical Image Analysis

Anomaly Detection Techniques and ApplicationsCutaneous Melanoma Detection and Management

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