Breakthrough Research Has Found That AI Can Detect These Health Conditions 10 Years Early

In an incredible breakthrough, Scottish researchers from the University Of Edinburgh collaborated with Biogen and Optima Partners and successfully used AI to identify protein markers in biological samples which are linked to three common diseases in the UK. 

The team explored a list of more than 20 diseases, including heart disease, which kills around 190 people per day, according to the British Heart Foundation. 

They also explored mental health conditions, including Alzheimer’s disease which is the UK’s biggest killer, according to Alzheimer’s Research UK.

GDF15, a marker of inflammation, was among some of the proteins under investigation and was found to be linked with almost half (eleven out of 23) of the diseases being studied.

These included dementia, heart disease, liver disease, type 2 diabetes and all-cause mortality.

Dr Danni Gadd, the first author of the study, said: “Our research represents a promising step forward in risk prediction. It’s encouraging to see how much potential there is from a single blood sample that allows us to predict a range of disease outcomes.”

1 in 2 of us will be affected by dementia in our lifetimes

According to Alzheimer’s Research UK: “One in two of us will be affected by dementia in our lifetime. Either by caring for someone with the condition, developing it ourselves, or both.”

Currently, 944,000 people are estimated to be living with dementia in the UK.

John Kinnear, the national director of Diabetes Scotlandsaid: “Diabetes is serious, and every diagnosis is life changing. It’s a relentless condition, and the fear of serious complications is a lifelong reality for people across Scotland.

“The latest Scottish Diabetes Survey figures show we’re in the grip of an escalating diabetes crisis, with rapidly increasing numbers of people now living with type 2 diabetes and millions at risk of developing the condition.”

He added that these findings offer hope as, “the earlier people at high risk are identified, the greater the opportunity to help them reduce their risk.”

 Here’s hoping.