AI will soon supplement and perhaps replace human specialists in fields such as radiology. Image via The Guardian

AI On Track to Revolutionize Healthcare, Starting With Diagnostic Technologies

One of the most promising –and disruptive– applications for AI technologies in the coming years and decades is in the field of medicine. AI-enabled technologies could revolutionize medicine and lead to more proactive, preventative care and vastly improved diagnostic outcomes. Leaders in the UK’s National Health Service –the state-funded healthcare program– have already begun to anticipate AI’s effects on the industry and are hopeful that AI will lead to computer-based diagnoses within a decade.

Computers could start diagnosing patients’ illnesses within the next few years as artificial intelligence increasingly ousts doctors from their traditional roles, NHS leaders believe.

NHS England plans to invest more of its £120bn budget in AI to speed up its application to medicine and the health service, especially the task of analysing “huge swaths” of the information collected from patients about their symptoms.

“We know from a number of studies that have been done that in, certain circumstances, AI is better than doctors at diagnosing certain conditions,” said Professor Sir Bruce Keogh, the organisation’s national medical director.

“All of this takes us into very new territory and it’s not a long way over there, it’s actually here now,” he told delegates at NHS England’s Health and Care Innovation Expo in Manchester.

Jeremy Hunt, the health secretary, said computers could be routinely diagnosing health conditions – even before they display symptoms – by the time the NHS turns 80 in 2028.

“The changes in medical innovation are likely to transform humanity by as much in the next 25 years as the internet has in the last 25 years,” he told the 5,000 delegates.

“So what might medicine look like when the NHS is 80? Well the first thing is we may well not be going to doctors for a diagnosis, we might be going to computers instead, who will be looking at the 300,000 biomarkers in every single drop of blood, mashing that with big data information about everyone else’s biomarkers,” he said.

Read more at the Guardian