"A causal perspective on dataset bias in machine learning for medical imaging"
C. Jones, D. C. Castro, F. Ribeiro, O. Oktay, M. McCradden, B. Glocker - Nature Machine Intelligence, 2024
"Exploring Scalable Medical Image Encoders Beyond Text Supervision".
F. Perez-Garcia*, H. Sharma*, S. Bond-Taylor*, ..., O. Oktay. - Nature Machine Intelligence, 2024
"RadEdit: stress-testing biomedical vision models via diffusion image editing"
F. Perez-Garcia, ..., M. Ilse*, O. Oktay* - ECCV, 2024
"Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing"
S. Bannur*, S. Hyland*, ..., O. Oktay - CVPR, 2023
"Exploring the Boundaries of GPT-4 in Radiology"
Q. Liu, ..., O. Oktay*, J. Alvarez-Valle* - EMNLP, 2023
"Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing".
B. Boecking*, N. Usuyama*, ..., O. Oktay - ECCV, 2022
"Active label cleaning for improved dataset quality under resource constraints".
M. Bernhardt, ..., O. Oktay - Nature Comms., 2022
"Attention gated networks: Learning to leverage salient regions in medical images".
O. Oktay*, J Schlemper*, ..., D. Rueckert - Medical Image Analysis, 2019
"Evaluating reinforcement learning agents for anatomical landmark detection".
A. Alansary, O. Oktay, ..., D. Rueckert - Medical Image Analysis, 2019
"Attention U-Net: Learning where to look for the pancreas".
O. Oktay*, J Schlemper*, ..., D. Rueckert - MIDL Conference, 2018