Using Big Data, Machine Learning to Reduce Chronic Disease Spending
Jessica Kent | September 18, 2018
Diabetes and heart disease are two of the most costly and prevalent chronic conditions impacting patients in the US, leading the healthcare industry to spend billions every year to treat and manage these disorders. As care delivery continues to evolve from reactive disease treatment to proactive, preventive care, more organizations are looking to advanced technologies like artificial intelligence and machine learning to assist with drawing actionable conclusions from their big data resources. Boston University’s College of Engineering is one such organization. “There is a lot of information about every one of us, in EHRs, in smart phones, in smart watches, and in other tracking devices,” Iaonnis Paschalidis, Professor of Engineering and Director of the Center for Information and Systems Engineering at Boston University, told HealthITAnalytics.com.