Advancing AI for healthcare
There are many exciting potential applications for AI in the stretched healthcare industry, particularly in the area of disease detection and prediction through the analysis of medical records and imaging exams. AI is already being applied to this area, but currently relies on high levels of input from medical experts to organise data and guide algorithms to identify anomalies.
Dr Tsaftaris’s Fellowship award will enable the development of advanced theory and computational methods to extract information and knowledge from healthcare records and imaging exams without the need for 'human' curation and supervision. The research promises to reduce healthcare costs and improve quality of care by assisting or automating current workflows.
Targeting cardiovascular disease
The ultimate aim of the project is to develop and translate advanced AI into 'clinician-ready' tools to detect and predict cardiovascular disease (CDV). CDV currently affects around 7 million people in the UK and last year accounted for a quarter of all deaths in the country.
Canon Medical collaboration
Dr Tsaftaris’s Fellowship is a partnership with the Royal Academy of Engineering and medical imaging equipment company Canon Medical, benefiting from close links with Canon Medical’s global Centre of Excellence for Healthcare AI in Edinburgh.
About Dr Sotirios Tsaftaris
Dr Tsaftaris is currently a Chancellor's Fellow and Reader at the School, and a Turing Fellow with the Alan Turing Institute. His research focuses on image analysis, data mining, machine learning, and distributed computing to address challenges in healthcare and global food supply.