The Madras Diabetes Research Foundation (MDRF) is set to leverage artificial intelligence, data science, and machine learning to enhance diabetes treatment. Collaborating with tech firm embedUR Systems, MDRF aims to utilize data from continuous glucose monitoring (CGM) patches to gain deeper insights into glucose variations.
MDRF Chairman V. Mohan announced that the institution will analyze data from CGM devices to explore if blood glucose fluctuations can predict type 1 or type 2 diabetes and potential complications. Dr. Mohan highlighted that, currently, only blood sugar levels are monitored, but the new data will help identify patterns that could refine treatment protocols.
Rajesh C. Subramaniam, CEO of embedUR Systems, explained that CGM devices use an Internet of Things (IoT) framework to collect data on glucose levels. The company’s engineers will analyze this data to identify markers such as low or high sugar events, which can then be used to develop predictive models for diabetes-related health issues.
As reported by The Hindu, Dr. Mohan compared this approach to advancements in human genome research, noting that non-hypothesis-based methods in genetics have previously identified key genes and pathways in diabetes that traditional methods missed. This initiative aims to similarly revolutionize diabetes treatment by uncovering critical insights through data analysis.