Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study K Dembrower, E Wåhlin, Y Liu, M Salim, K Smith, P Lindholm, M Eklund, ... The Lancet Digital Health 2 (9), e468-e474, 2020 | 234 | 2020 |
External evaluation of 3 commercial artificial intelligence algorithms for independent assessment of screening mammograms M Salim, E Wåhlin, K Dembrower, E Azavedo, T Foukakis, Y Liu, K Smith, ... JAMA oncology 6 (10), 1581-1588, 2020 | 228 | 2020 |
Comparison of a deep learning risk score and standard mammographic density score for breast cancer risk prediction K Dembrower, Y Liu, H Azizpour, M Eklund, K Smith, P Lindholm, F Strand Radiology 294 (2), 265-272, 2020 | 143 | 2020 |
Patchdropout: Economizing vision transformers using patch dropout Y Liu, C Matsoukas, F Strand, H Azizpour, K Smith Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 29 | 2023 |
Adding seemingly uninformative labels helps in low data regimes C Matsoukas, AB Hernandez, Y Liu, K Dembrower, G Miranda, E Konuk, ... International Conference on Machine Learning, 6775-6784, 2020 | 21 | 2020 |
Decoupling inherent risk and early cancer signs in image-based breast cancer risk models Y Liu, H Azizpour, F Strand, K Smith Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 15 | 2020 |
Csaw-m: An ordinal classification dataset for benchmarking mammographic masking of cancer M Sorkhei, Y Liu, H Azizpour, E Azavedo, K Dembrower, D Ntoula, ... arXiv preprint arXiv:2112.01330, 2021 | 13 | 2021 |
Recurrent knowledge distillation SL Pintea, Y Liu, JC van Gemert 2018 25th IEEE International Conference on Image Processing (ICIP), 3393-3397, 2018 | 3 | 2018 |