We hear a great deal about artificial intelligence or AI , which generally taken mean processes where a machine mimics cognitive functions normally associated with human minds, such as learning, language processing and problem solving.
In relation to the extent of successful practical applications so far achieved, we may be hearing rather too much too soon: we may even be seeing a level of hype not seen since the “dot com” boom and bust of the early 2000’s. But in healthcare expectations for AI run high, with an estimated 15% of all AI investment going into health applications, and health accounting for nearly half of all AI companies valued at over $1 billion.
What will all this do for us? At the moment, we are seeing mainly automated symptom checkers, ranging from simple searches of Dr Google, to interactive systems based on “primary care assistants” such as Babylon. Such advances, if they gain public confidence, could ease the burden of triaging and attending to the needs of increasingly old and sick populations, at a time of growing staff shortages. But the real opportunity lies with data analytics.
We need to devise machines which extract, connect and structure the wealth of genetic and other patient data suddenly available to us, to fight cancer and the delay the onset of dread diseases of the central nervous system.