Artificial intelligence to improve cancer diagnosis

Diagnosis

Ovarian Cancer Action welcomes today’s announcement from the Prime Minister to use emerging technologies to transform cancer diagnosis in the UK, saving around 22,000 lives a year by 2033.



Artifical Intelligence and big data could be used to cross reference people’s genes, habits and medical records with national data, allowing doctors to make earlier referrals for a number of cancers and other chronic diseases.

“Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths”, the Prime Minister said.

It is thought that by utilising this technology, at least 50,000 people every year with ovarian, bowel, prostate, or lung cancer will be given an earlier diagnosis. 

Cary Wakefield, Chief Executive of Ovarian Cancer Action, said: “Currently in the UK, only 46% of women diagnosed with ovarian cancer will survive beyond five years. Early detection and diagnosis are vital for improving survival rates and we welcome the Government highlighting the need for innovation in medical research to advance cancer outcomes in the UK.

Artificial Intelligence has accelerated exciting new advances in other disease areas such as Motor Neurone disease; this same progress is much needed in ovarian cancer where survival rates have not changed in over 20 years. As the UK’s ovarian cancer research charity, we are pushing the boundaries of ovarian cancer research, bringing together new technologies with world class research to find the much-needed breakthrough to stop women dying before their time.”

As the UK’s ovarian cancer research charity, Ovarian Cancer Action has a long history of funding innovative research through the Ovarian Cancer Action Research Centre and our HHMT symposium, bringing together the world’s experts to look forward to the future of ovarian cancer research in collaboration with the latest cutting edge technology.


Sign our petition for the UK Government to carry out an ovarian cancer audit to improve survival rates.