Image: The UK Prime Minister Theresa May wants to use AI to battle cancer (Photo courtesy of Getty Images).
Theresa May, Prime Minister of the United Kingdom, is aiming to cut cancer deaths by 10% using artificial intelligence (AI) as the key driver of improved health outcomes.
The ambitious new plan calls for the National Health Service (NHS, London), the AI industrial sector, and health charities to use data and AI to transform the diagnosis of chronic diseases, with the goal of seeing around 22,000 fewer people dying from cancer each year by 2033. The plans will see at least 50,000 people each year diagnosed at an early stage of prostate, ovarian, lung, or bowel cancer through the use of emerging technologies that will cross-reference people’s genetics, habits, and medical records with national data to spot those at an early stage of cancer.
“The development of smart technologies to analyze 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 armory in the fight against disease,” said Prime Minister May. “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 centers of excellence in places like Edinburgh, Oxford, and Leeds, and helping to grow new ones.”
“Earlier detection and diagnosis could fundamentally transform outcomes for people with cancer, as well as saving the NHS money. The Government’s mission to revolutionize healthcare using the power of artificial intelligence is pioneering,” said Sir Harpal Kumar, CEO of Cancer Research (London, United Kingdom). “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.”
“There is promising evidence that using artificial intelligence to analyze MRI scans could spot early signs of heart disease which may be missed by current techniques,” added Simon Gillespie, CEO of the British Heart Foundation (Birmingham, United Kingdom). “This could lead to a quicker diagnosis with more personalized treatment that could ultimately save lives.”
Most of the information in clinics and medical practices is stored digitally, but image data, findings, lab values, digital patient records, and surgery reports have all been handled separately. But current trends are encouraging data integration into one unified software framework that will enable faster handling of medical information, and will lay the foundation for more efficient interaction between different specialties and enable more precise and personalized clinical decisions.
National Health Service
British Heart Foundation