Now comes an AI tool to manage diabetes

Mumbai: In a groundbreaking research, the National Institute of Technology at Rourkela has developed an AI-powered model to improve blood sugar predictions for diabetes management.

The model learns from past glucose trends, insulin dosage, meal information and physical activity data, providing more accurate forecasts without needing complex adjustments.

It could help patients and doctors make better treatment decisions and integrate with smart health devices, including mobile phones.

Unlike traditional forecasting models, which often struggle with long-term trends and require manual adjustments, this model processes glucose data automatically, identifying key patterns and making precise predictions.

The NIT-Rourkela team was led by Prof Mirza Khalid Baig, Assistant Professor, Biotechnology and Medical Engineering.

Prof Baig co-authored the paper with research scholar Deepjyoti Kalita - and it has been published by IEEE Journal of Biomedical and Health Informatics.

“According to the results of ICMR INDIAB study released in 2023, the overall prevalence of diabetes in our country is 11.4% and that of prediabetes is 15.3%. Hence, it is crucial that we develop new solutions to tackle this problem. Our core innovation lies in using multi-head attention layers within a neural basis expansion network, which allows the model to focus on the most relevant data points while ignoring unnecessary noise. This results in better performance without the need for large amounts of training data or extensive computing power,” said Prof Baig.

“By combining precision with efficiency, we aim to provide a practical tool that can be integrated into digital health solutions, helping patients and doctors manage diabetes more effectively,” he added.

Diabetes is a major health challenge in India, with cases expected to reach 124.9 million by 2045. Effective diabetes management relies on regular glucose monitoring to prevent dangerous spikes (hyperglycemia) and drops (hypoglycemia) in blood sugar levels.

Managing diabetes can be difficult due to a lack of specialists, unequal access to healthcare, low medication adherence, and poor self-care. These challenges make it harder for patients to keep their blood sugar levels under control, increasing the risk of serious health problems.

New digital health technologies, especially those that use Artificial Intelligence (AI), offer a way to improve diabetes care and reduce costs.

Machine learning (ML) has been used in many areas of diabetes research, from basic studies to predictive tools that can help doctors and patients make better and timely decisions. However, AI learning models, especially predictive AI models, have a few drawbacks. Many of these models work like a “black box,” meaning their predictions are difficult to understand. This lack of transparency makes it hard for doctors and patients to fully trust them. Furthermore, traditional models, such as statistical forecasting methods or basic neural networks, often fail to recognise long-term glucose fluctuations and require complex fine-tuning.