Diabetes is a major health challenge in India, with cases expected to reach 149 million by 2045. There are areas of diabetes management that are effective with regular glucose monitoring to prevent dangerous spikes (hyperglycemia) and hypoglycemia (hyperglycemia) in blood glucose levels. Management of diabetes is difficult due to a shortage of professionals, unequal access to healthcare, low medication and poor self-care. These challenges make it difficult for patients to continue to control their blood glucose levels and increase the risk of serious health problems.New digital health technologies, particularly those using artificial intelligence (AI), provide ways to improve diabetes care and reduce costs. Machine learning (ML) is used in many areas of diabetes research, from basic research to predictive tools that help physicians and patients make better and timely decisions. However, AI learning models, in particular predictive AI models, have some drawbacks. Many of these models work like “black boxes.” In other words, it is difficult to understand predictions. This lack of transparency makes it difficult for doctors and patients to trust them completely. Furthermore, traditional models such as statistical prediction methods and basic neural networks cannot recognize long-term glucose fluctuations and require complex fine-tuning.A research team at the National Institute of Technology, led by Professor Mirza Khalid Baig, an assistant professor in biotechnology and medical engineering, has developed a new AI-driven approach to improving blood glucose prediction in diabetic patients.The results of this study are published in the prestigious IEEE Journal of Biomedical and Health Informatics.Researchers at NIT Rourkela focused on improving glucose prediction using deep learning techniques. Their approach incorporates specialized AI models that learn from past blood glucose trends and predict future levels more accurately than existing methods. Unlike traditional prediction models that often struggle with long-term trends and require manual adjustments, this model automatically processes glucose data, identifying important patterns and making accurate predictions.“According to the results of the ICMR IndiaB study published in 2023, the overall prevalence of diabetes in our country is 11.4% and the result of diabetes in diabetes is 15.3%. Therefore, it is important to develop new solutions to tackle this problem. This will improve performance without the need for large amounts of training data or large computing power. We aim to provide practical tools that can be integrated into digital health solutions.