There are many exciting potential applications for AI in the stretched healthcare industry, particularly in disease detection and prediction through the analysis of medical records and imaging exams. AI is already prominent in this area but currently relies on high input levels from medical experts to organise data and guide algorithms to identify anomalies.
Our research 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 the quality of care by assisting or automating current workflows.
Our performance in everyday noisy situations is known to depend on aural and visual senses. The ‘multi-modal’ nature of speech perception has been confirmed by research, which has established that listeners unconsciously lip-read to improve the intelligibility of signals amid background noise.