Smartphone and wearable data, such as heart rate, activity, and sleep patterns, can significantly enhance cardiovascular disease research and treatment by offering insights into disease development, improving monitoring and management, and identifying key health metrics. This data, categorized into passive (e.g., step count) and active (e.g., self-reported quality-of-life scores), becomes more impactful when linked to medical records. Public participation is critical, necessitating trust-building and inclusive study designs. aiHealth Lab is advancing cardiovascular health by leveraging these technologies securely, addressing privacy and health disparities, and fostering public engagement.

AI is applied to image-based data to improve clinical decision-making processes, extend the reach of imaging tools, and enhance their precision and accuracy.

The Diabetes Data Science Catalyst will support research of relevance to both diabetes and cardiovascular diseases through the use of health data science and advanced analytics such as Artificial Intelligence.  We are actively seeking collaborations to enhance research and understanding of the link between cardiovascular diseases and diabetes in Bangladesh, aiming to improve healthcare outcomes through data-driven approaches.

We are actively seeking collaborations through the Stroke Data Science Catalyst to enhance research on stroke in Bangladesh. Our goal is to leverage data science to improve the understanding, prevention, and treatment of stroke, ultimately advancing healthcare outcomes nationwide.