Ai Tool Predicts Type 1 Diabetes Risk from Blood | Learn the risk of diabetes in future from artificial intelligence

Researchers at Western Sydney University have created this device. This device not only assesses the risk of being type 1 diabetes, but can also explain how the person’s body will react to the treatment of the disease. This device uses ‘Dynamic Risk Score’ (DRS4C), which suggests whether a person has type 1 diabetes. This device is based on microRNA. It contains pieces of very small RNA measured by blood, which help in catching the risk of type 1 diabetes.

Anand Hardikar, Professor of the University School of Medicine and Translational Health Research Institute, said that it is very important to know the risk of type 1 diabetes in advance. Because now such medicines have become available which can slow down the process of increasing disease. Especially in children, who suffer from this disease before the age of 10 years, this disease grows very fast and can reduce the age of people living for about 16 years. Therefore, it is important for the doctor to find out the disease at the right time.

Published in Nature Medicine magazine, this research analyzed samples of about 5,983 people from countries like India, Australia, Canada, Denmark, Hong Kong, New Zealand, and America. The researchers then tested it on 662 more people, so that it would be known whether this score is doing the right thing. Just one hour after starting treatment, the score said that who with type 1 diabetes will be able to recover without insulin.

This is not limited to knowing just the risk of type 1 diabetes and the effect of medicines. Dr. Mugdha Joglekar, head researcher at the University’s School of Medicine and Translational Health Research Institute, discovered the difference between two types of threats between the genetic risk markers and the dynamic risk marker. Genetic risk marker means signs from genes. At the same time, dynamic risk marker means signs that keep changing with time. Dr. Joglekar said that genetic testing gives just an old or stable information, while dynamic risk markers help in understanding the risk of disease better.