In the UK alone, currently 7 million people live with cardiovascular disease and this number will increase as the population ages. Under-resourced and under-staffed healthcare systems are struggling with the rising caseload and the large volumes of information being generated. Currently, excitement in Artificial Intelligence (AI) for healthcare is high, because of its potential to help stem this information overload and reduce healthcare costs.
The AI paradigm fuelling this excitement heavily depends on well-curated training data and is largely seen as a black box. In contrast we will:
- learn from complex, multimodal, healthcare records with minimal supervision; and
- focus on problems underpinning learning data representations optimised to provide a transparent base for the desired diagnoses and predictions. We will then translate these techniques to automated estimation of cardiac biomarkers, disease diagnosis, and most ambitiously, cardiac episode prediction, thus opening roads to preventive care.
Keynote: Doing More with Less by Disentangled Data Representations, Keynote DART, MICCAI, October 2020.
Tutorial: DREAM: Disentangled Representations for Efficient Algorithms for Medical data, MICCAI Tutorial, MICCAI, October 2020.
Event: Sotos invited to present at The Global AI Summit, organized by the Saudi Data and Artificial Intelligence Authority, March 2020. [postponed due to COVID-19]
News: How can AI help? Reading the language of medicine, Canon Medical Blog, October 2019.
Event: Public Event in Japan, British Embassy. AI and Healthcare, October 2019.
Keynote: Disentangled Representation Learning in Medical Imaging, Keynote STACOM, MICCAI, October 2019.
Tutorial: Simulation and Synthesis, Tutorial at International Conference on Acoustics Speech and Signal Processing (ICASSP), May 2019.
News: Interview in Greek Huffington Post, September 2019.
News: How can AI help? Reading the language of medicine, Canon Medical Blog, (link)
Event: Intervention at Future-proofing society – how digital health and social care can empower and transform lives, Scottish Parliament and IET Event.
News: Prof. Tsaftaris featured in School of Engineering News.
News: Prof. Tsaftaris featured in RAEng News.
Kick-off: We started a new project.
3. Have you forgotten? A method to assess if machine learning models have forgotten data
X. Liu, S.A. Tsaftaris
6. Disentangled Representations for Domain-generalized Cardiac Segmentation
X. Liu, S. Thermos, A. Chartsias, A.Q. O'Neil, S.A. Tsaftaris
MICCAI 2020, STACOM: Statistical Atlases and Computational Modelling of the Heart
7. Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling
H. Jiang, C. Wang, A. Chartsias, S.A. Tsaftaris
MICCAI 2020, MyoPS: Multi-sequence CMR based Mycardial Pathology Segmentation Challenge
8. Semi-supervised Pathology Segmentation with Disentangled Representations
H. Jiang, A. Chartsias, X. Zhang, G. Panastasiou, S. Semple, M. Dweck, D. Semple, R. Dharmakumar, S.A. Tsaftaris
MICCAI 2020, DART: Domain Adaptation and Representation Transfer
10. Multimodal cardiac segmentation using disentangled representations
A. Chartsias, G. Papanastasiou, C. Wang, C. Stirrat, S. Semple, D. Newby, R. Dharmakumar, S.A. Tsaftaris
MICCAI 2019, STACOM: Statistical Atlases and Computational Models of the Heart
11. Temporal Consistency Objectives Regularize the Learning of Disentangled Representations
G. Valvano, A. Chartsias, A. Leo, S.A. Tsaftaris
MICCAI 2019, DART: Domain Adaptation and Representation Transfer
12. Conditioning Convolutional Segmentation Architectures with Non-Imaging Data
G. Jacenków, A. Chartsias, B. Mohr, S.A. Tsaftaris
- Prof. Sotirios Tsaftaris The University of Edinburgh (Principal Investigator)
- Prof. Dave Newby The University of Edinburgh (Clinical Collaborator)
- Dr Scott Semple The University of Edinburgh (Clinical Collaborator)
- Prof. Rohan Dharmakumar Cedars-Sinai Medical Center (Clinical Collaborator)
- Dr Spyridon Thermos The University of Edinburgh (Research Associate)
- Mr Agisilaos Chartsias The University of Edinburgh (PhD Student)
- Mr Grzegorz Jacenków The University of Edinburgh (PhD Student)
- Mr Xiao Liu The University of Edinburgh (PhD Student)
- Dr Giorgos Papanastasiou The University of Essex (Clinical Collaborator)
- Dr Ken Sutherland Canon Research Europe Ltd. (President, Industry Partner)
- Dr Andy Smout Canon Research Europe Ltd. (Vice-President, Industry Partner)
- Dr Alison O’Neil Canon Research Europe Ltd. (Senior AI Scientist, Industry Partner)
- Dr Sandy Weir Canon Research Europe Ltd. (Technical Manager, Industry Partner)
Generously supported by Canon Medical Research Europe, the Royal Academy of Engineering and the School of Engineering.