Artificial intelligence (AI) has been used to predict a person’s risk of developing conditions such as Alzheimer’s and heart disease up to 10 years before a diagnosis.
Scientists in the United Kingdom used cutting-edge technology to analyse blood samples from the UK Biobank, a database of genetic and health information.
Managing Director and Chief Scientist of Optima Partners Dr Chris Foley said researchers used machine learning to study blood samples from more than 45,000 people.
Dr Foley said AI tools were able to identify patterns of proteins present in the blood linked to increased risk of disease, allowing researchers to accurately predict a person’s probability of developing a condition before symptoms appear.
He said being able to detect early warning signs for a broad set of conditions may lead to opportunities for early intervention and prevention.
“The team used AI and machine learning tools to identify protein patterns in the blood that were indicative of the development of common conditions including Alzheimer’s, heart disease and type 2 diabetes.”
Dr Foley said the disease diagnosis information was taken from the medical records of the participants up to 10 years after the blood sample measurements.
“More work is still needed to convert these findings for practical use in clinical settings. However, our discoveries set strong foundations for the inclusion of new risk prediction signatures to shed light on possible pathways and mechanisms that underlie diseases.”
He said pattern recognition like this would not be possible without modern machine learning technology.
Read the full study in Nature Aging.
