An AI-driven algorithm has been created by researchers at NIT Rourkela to enhance blood sugar forecasts for diabetics. By improving accuracy, this machine-learning method makes it possible to make better, more individualised treatment choices.
The research offers a machine-learning model that improves blood glucose level prediction accuracy, assisting patients and medical professionals in making more informed and individualised treatment choices, explained that the institute.
About the Research:
Lack of specialists, unequal access to healthcare, poor self-care, and low medication adherence can all make managing diabetes challenging. Patients find it more difficult to control their blood sugar levels as a result of these difficulties, which raises the possibility of major health issues.
The goal of the NIT Rourkela team was to employ deep learning methods to improve glucose forecasting. Their strategy uses a customised artificial intelligence model that learns from historical blood sugar patterns and forecasts levels more precisely than current techniques.
This algorithm analyses glucose data automatically, spotting important patterns and producing accurate predictions, in contrast to typical forecasting methods that frequently struggle with long-term trends and need manual changes.
Through a variety of applications, an AI-driven strategy may eventually improve diabetes care. It might be utilised in clinical settings to assist physicians in creating individualised treatment programs, integrated into mobile health apps for real-time glucose tracking, or connected into smart insulin pumps to automate insulin delivery.
