Vivek Natarajan
Vivek Natarajan
Research Lead, Google Health AI
Verified email at - Homepage
Cited by
Cited by
Large language models encode clinical knowledge
K Singhal, S Azizi, T Tu, SS Mahdavi, J Wei, HW Chung, N Scales, ...
Nature 620 (7972), 172-180, 2023
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research 23 (226), 1-61, 2022
Towards vqa models that can read
A Singh, V Natarajan, M Shah, Y Jiang, X Chen, D Batra, D Parikh, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
A deep learning system for differential diagnosis of skin diseases
Y Liu, A Jain, C Eng, DH Way, K Lee, P Bui, K Kanada, ...
Nature medicine 26 (6), 900-908, 2020
Big self-supervised models advance medical image classification
S Azizi, B Mustafa, F Ryan, Z Beaver, J Freyberg, J Deaton, A Loh, ...
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
Towards expert-level medical question answering with large language models
K Singhal, T Tu, J Gottweis, R Sayres, E Wulczyn, L Hou, K Clark, S Pfohl, ...
arXiv preprint arXiv:2305.09617, 2023
Contrastive training for improved out-of-distribution detection
J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ...
arXiv preprint arXiv:2007.05566, 2020
Pythia v0. 1: the winning entry to the vqa challenge 2018
Y Jiang, V Natarajan, X Chen, M Rohrbach, D Batra, D Parikh
arXiv preprint arXiv:1807.09956, 2018
Pythia-A platform for vision & language research
A Singh, V Natarajan, Y Jiang, X Chen, M Shah, M Rohrbach, D Batra, ...
Towards generalist biomedical ai
T Tu, S Azizi, D Driess, M Schaekermann, M Amin, PC Chang, A Carroll, ...
NEJM AI 1 (3), AIoa2300138, 2024
Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions
AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ...
Medical Image Analysis 75, 102274, 2022
Dermgan: Synthetic generation of clinical skin images with pathology
A Ghorbani, V Natarajan, D Coz, Y Liu
Machine learning for health workshop, 155-170, 2020
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ...
Nature Biomedical Engineering 7 (6), 756-779, 2023
Supervised transfer learning at scale for medical imaging
B Mustafa, A Loh, J Freyberg, P MacWilliams, M Wilson, SM McKinney, ...
arXiv preprint arXiv:2101.05913, 2021
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications
J Schrouff, N Harris, O Koyejo, I Alabdulmohsin, E Schnider, ...
arXiv preprint arXiv:2202.01034, 2022
Building Customized User Profiles Based on Conversational Data
V Natarajan, W Yang, LIU Honglei, A Kumar
US Patent App. 15/967,239, 2019
Robust and efficient medical imaging with self-supervision
S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ...
arXiv preprint arXiv:2205.09723, 2022
Towards conversational diagnostic ai
T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ...
arXiv preprint arXiv:2401.05654, 2024
Medperf: open benchmarking platform for medical artificial intelligence using federated evaluation
A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, S Bala, ...
arXiv preprint arXiv:2110.01406, 2021
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
K Dvijotham, J Winkens, M Barsbey, S Ghaisas, R Stanforth, N Pawlowski, ...
Nature Medicine 29 (7), 1814-1820, 2023
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