Ageing in the age of big data

Our ageing society requires novel approaches to support self-determined lives up to an old age. I argue that big data analysis will take on a prominent role in addressing this challenge. By making use of the unprecedented availability of data on all aspects of human behaviour, medical informatics can, first, monitor and predict disease progression in individual patients, second, identify factors that causally contribute to behavioural deficits, and, third, translate these findings into novel preventative measures and clinical therapies. I illustrate these concepts on the prediction of disease progression from large-scale clinical data in amyotrophic lateral sclerosis (ALS), causal inference on the neural basis of behaviour, brain-computer interfacing for communication with locked-in patients, and brain-controlled robotics for stroke rehabilitation. In combination with advances in wearable sensors and in ubiquitous computing, medical informatics for big data analysis will revolutionise our healthcare system.