Paschalidis Shares Health Data Findings in DeLisi Lecture

Professor Yannis Paschalidis (ECE, BME, SE) discussed data-driven reasoning—which he calls “the backbone of engineering systems”—and predictive health analytics as he delivered the Charles DeLisi Distinguished Lecture May 6 to an online audience of about 100 members of the Boston University community. The DeLisi Award and Lecture honors a senior faculty member engaged in outstanding […]

Tagged: , ,

Using Big Data, Machine Learning to Reduce Chronic Disease Spending

“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, Director of the Center for Information and Systems Engineering and Systems Engineering Professor, told HealthITAnalytics.com. “We can now analyze what happens to patients in real time and characterize the status and health condition of each individual.”

Researchers Win $900k NSF Grant to Predict Heart Disease, Diabetes Using Machine Learning

By Maureen Stanton, CISE Researchers from the College of Engineering and Boston Medical Center (BMC) will use a three-year, $900,000 grant from the National Science Foundation to develop and pilot a health informatics system to predict patients at risk of heart disease or diabetes, and enable early intervention and personalized treatment. “Our research vision is […]

Cassandras, Paschalidis Lend Smart Cities Knowledge to Special Issue of Proceedings of the IEEE

Professor Christos Cassandras (ECE, SE) was invited to be one of three guest editors on the April 2018 issue of the Proceedings of the IEEE on smart cities; he also co-authored one of the papers along with Professor Ioannis Paschalidis (ECE, BME, SE), who co-authored two.