Zobrazeno 1 - 10
of 205
pro vyhledávání: '"McCarthy, Davis"'
Autor:
Wang, Chong, Chen, Yuanhong, Liu, Fengbei, Liu, Yuyuan, McCarthy, Davis James, Frazer, Helen, Carneiro, Gustavo
Prototypical-part methods, e.g., ProtoPNet, enhance interpretability in image recognition by linking predictions to training prototypes, thereby offering intuitive insights into their decision-making. Existing methods, which rely on a point-based lea
Externí odkaz:
http://arxiv.org/abs/2312.00092
The ADMANI datasets (annotated digital mammograms and associated non-image datasets) from the Transforming Breast Cancer Screening with AI programme (BRAIx) run by BreastScreen Victoria in Australia are multi-centre, large scale, clinically curated,
Externí odkaz:
http://arxiv.org/abs/2305.12068
Autor:
Chen, Yuanhong, Liu, Yuyuan, Wang, Chong, Elliott, Michael, Kwok, Chun Fung, Pena-Solorzano, Carlos, Tian, Yu, Liu, Fengbei, Frazer, Helen, McCarthy, Davis J., Carneiro, Gustavo
Methods to detect malignant lesions from screening mammograms are usually trained with fully annotated datasets, where images are labelled with the localisation and classification of cancerous lesions. However, real-world screening mammogram datasets
Externí odkaz:
http://arxiv.org/abs/2301.13418
Autor:
Wang, Chong, Liu, Yuyuan, Chen, Yuanhong, Liu, Fengbei, Tian, Yu, McCarthy, Davis J., Frazer, Helen, Carneiro, Gustavo
Prototypical part network (ProtoPNet) methods have been designed to achieve interpretable classification by associating predictions with a set of training prototypes, which we refer to as trivial prototypes because they are trained to lie far from th
Externí odkaz:
http://arxiv.org/abs/2301.04011
Autor:
Wang, Chong, Chen, Yuanhong, Liu, Yuyuan, Tian, Yu, Liu, Fengbei, McCarthy, Davis J., Elliott, Michael, Frazer, Helen, Carneiro, Gustavo
State-of-the-art (SOTA) deep learning mammogram classifiers, trained with weakly-labelled images, often rely on global models that produce predictions with limited interpretability, which is a key barrier to their successful translation into clinical
Externí odkaz:
http://arxiv.org/abs/2209.12420
Autor:
Chen, Yuanhong, Wang, Hu, Wang, Chong, Tian, Yu, Liu, Fengbei, Elliott, Michael, McCarthy, Davis J., Frazer, Helen, Carneiro, Gustavo
When analysing screening mammograms, radiologists can naturally process information across two ipsilateral views of each breast, namely the cranio-caudal (CC) and mediolateral-oblique (MLO) views. These multiple related images provide complementary d
Externí odkaz:
http://arxiv.org/abs/2209.10478
Autor:
Ibeh, Neke, Kusuma, Pradiptajati, Crenna Darusallam, Chelzie, Malik, Safarina G., Sudoyo, Herawati, McCarthy, Davis J., Gallego Romero, Irene
Publikováno v:
In The American Journal of Human Genetics 7 November 2024 111(11):2458-2477
Autor:
Chen, Yuanhong, Liu, Yuyuan, Wang, Chong, Elliott, Michael, Kwok, Chun Fung, Peña-Solorzano, Carlos, Tian, Yu, Liu, Fengbei, Frazer, Helen, McCarthy, Davis J., Carneiro, Gustavo
Publikováno v:
In Medical Image Analysis August 2024 96
Autor:
Tsui, Vanessa, Lyu, Ruqian, Novakovic, Stevan, Stringer, Jessica M., Dunleavy, Jessica E.M., Granger, Elissah, Semple, Tim, Leichter, Anna, Martelotto, Luciano G., Merriner, D. Jo, Liu, Ruijie, McNeill, Lucy, Zerafa, Nadeen, Hoffmann, Eva R., O’Bryan, Moira K., Hutt, Karla, Deans, Andrew J., Heierhorst, Jörg, McCarthy, Davis J., Crismani, Wayne
Publikováno v:
In Cell Genomics 9 August 2023 3(8)
Autor:
McCarthy, Davis James
Understanding the structure and function of genomic variation within and be- tween individuals will be crucial for the translation of genomics into improved health and clinical outcomes. This thesis addresses current issues around the study of genomi
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.712467