Artificial intelligence in medicine: current trends and future possibilities

Informing clinical decision making through insights from past data is the essence of evidence-based medicine. Traditionally, statistical methods have approached this task by characterising patterns within data as mathematical equations, for example, linear regression suggests a'line of best fit'. Through'machine learning' (ML), AI provides techniques that uncover complex associations which cannot easily be reduced to an equation. For example, neural networks represent data through vast numbers of interconnected neurones in a similar fashion to the human brain. This allows ML systems to approach complex problem solving just as a clinician might -- by carefully weighing evidence to reach reasoned conclusions.