On Thursday 26 April 2018, 120 researchers from across Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø were brought together for the first event from the Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Cancer Domain - Artificial Intelligence in Cancer Research.
The event brought the community together to identify innovative uses of AI and advanced analytic methodologies, and consider societal, medical and ethical implications, as well as discuss opportunities and challenges around data access. Â
For those who weren't able to make the event, a selection of the PowerPoint presentations have been published below, and you can  for a selection of tweets to give you a flavour of the afternoon!
Speakers:
-  (Senior Researcher in Electronic Health Records, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Institute of Health Informatics) - 'Use of large scale electronic health records in cancer research'ÌýÌý
- (Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Department of Computer Science)
- (Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Cancer Institute) - 'Using data from cancer clinical trials'
- (Lecturer, Centre for Medical Image Computing, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Department of Medical Physics and Biomedical Engineering) - 'The Data Analytics for RadioTherapy (DART) platform'
- Natalie Holroyd (PhD student, Centre for Advanced Biomedical Imaging, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Division of Medicine) -Ìý'High Resolution Episcopic Microscopy as a tool for probing the tumour microenvironment'
- Dr Guotai Wang (Research Associate, Medical Physics and Biomedical Engineering, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Centre for Medical Imaging Computing) - 'Automatic brain tumor segmentation using cascaded anisotropic convolutional neural networks'
- Dr Mae Woods (Research Associate, Research Department of Cell and Developmental Biology, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Division of Biosciences) - 'Large structural variation and the maximum threshold in cancer'
- Jeff Newell (Director of Applied Research for ) - 'AI for Oncology at Varian'
- (Centre for Advanced Biomedical Imaging, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Division of Medicine) - 'What can't we do with machine learning in biomedical imaging?'
- (Lecturer in Computational Cancer Biology, Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Department of Genetics, Evolution and Environment) - 'Learning cancer development trajectories and tumour microenvironment impact from genomic data'
- (Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø Cancer Institute)