Ambitious new plans set out by the Prime Minister saw around 22,000 fewer people dying from cancer each year by 2033.
Speaking in Macclesfield, the Prime Minister used a speech to challenge the NHS, Artificial Intelligence (AI) sector and health charities to use data and AI to transform the diagnosis of chronic diseases.
The plans will see at least 50,000 people each year diagnosed at an early stage of prostate, ovarian, lung or bowel cancer – people who would have otherwise been diagnosed at a later and more deadly stage.
This would be done through using emerging technologies to cross reference people’s genetics, habits and medical records with national data to spot those at an early stage of cancer – empowering doctors to make referrals to an oncologist earlier and even ahead of clear symptoms developing.
The Prime Minister said: 'Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths.
'And the development of smart technologies to analyse great quantities of data quickly and with a higher degree of accuracy than is possible by human beings opens up a whole new field of medical research and gives us a new weapon in our armoury in the fight against disease.
'Achieving this mission will not only save thousands of lives. It will incubate a whole new industry around AI-in-healthcare, creating high-skilled science jobs across the country, drawing on existing centres of excellence in places like Edinburgh, Oxford and Leeds – and helping to grow new ones.'
Sir Harpal Kumar, CEO of Cancer Research said: 'Earlier detection and diagnosis could fundamentally transform outcomes for people with cancer, as well as saving the NHS money. The Government’s mission to revolutionise healthcare using the power of artificial intelligence is pioneering. Advances in detection technologies depend on the intelligent use of data and have the potential to save hundreds of thousands of lives every year. We need to ensure we have the right infrastructure, embedded in our health system, to make this possible.'