Click For Photo: https://i.dailymail.co.uk/1s/2019/05/13/09/13431884-0-image-a-3_1557737635161.jpgClick For Video: https://videos.dailymail.co.uk/video/mol/2019/04/17/547715065140327918/1024x576_MP4_547715065140327918.mp4
Algorithms similar to those employed by Netflix and Spotify to customise services are now better than human doctors at spotting who will die or have a heart attack.
Machine learning was used to train LogitBoost, which its developers say can predict death or heart attacks with 90 per cent accuracy.
Variables - Risk - Health - Patients - Scans
It was programmed to use 85 variables to calculate the risk to the health of the 950 patients that it was fed scans and data from.
Patients complaining of chest pain were subjected to a host of scans and tests before being treated by traditional methods.
Data - Algorithm
Their data was later used to train the algorithm.
It 'learned' the risks and, during the six-year follow-up, had a 90 per cent success rate at predicting 24 heart attacks and 49 deaths from any cause.
Services - Netflix - Spotify - Systems - Algorithms
Services like Netflix and Spotify systems all use algorithms in a similar way to adapt to individual users and offer a more personalised look.
Study author Dr Luis Eduardo Juarez-Orozco, of the Turku PET Centre, Finland, said these advances go beyond medicine.
Advances - Medicine - Risk - Outcomes
He said: 'These advances are far beyond what has been done in medicine, where we need to be cautious about how we evaluate risk and outcomes.
'We have the data but we are not using it to its full potential yet.'
Doctors - Risk - Scores - Treatment - Decisions
Doctors use risk scores to make treatment decisions - but these scores are based on just a 'handful' of variables in patients.
Through repetition and adjustment, machines use large amounts of data to identify complex patterns not evident to humans.
Dr - Juarez-Orozco
Dr Juarez-Orozco said:...
Wake Up To Breaking News!