Notre Dame CARE: Collaborative Assessment Recommendation Engine personalized disease risk predictions
U. of Notre Dame researchers have developed a computer-aided method that uses electronic medical records to offer the promise of rapid advances toward personalized health care, disease management and wellness.
Science Daily, July 25, 2013.
Notre Dame computer science associate professor Nitesh V. Chawla and his doctoral student, Darcy A. Davis, developed the system called Collaborative Assessment and Recommendation Engine (CARE) for personalized disease risk predictions and well-being.
“The potential for ‘personalizing’ health care from a disease prevention, disease management and therapeutics perspective is increasing,” Chawla said. “Health care informatics and advanced analytics, or data science, may contribute to this shift from
population-based evidence for health care decision-making to the
fusion of population- and individual-based evidence in health care.
The key question is how to leverage health population data to drive patient-centered health care.”
At the heart of CARE is a novel collaborative filtering method that captures patient similarities and produces personalized disease risk profiles for individuals. Using what is known as Big Data science, the system generates predictions focused on other diseases that are based on Big Data from similar patients.
“In its most conservative use, the CARE rankings can provide reminders for conditions that busy doctors may have overlooked,” Chawla said. “Utilized to its full potential, CARE can be used to explore broader disease histories, suggest previously unconsidered concerns and facilitate discussion about early testing and prevention, as well as wellness strategies that may ring a more familiar bell with an individual and are essentially doable.
A paper by Chawla and Davis, Bringing Big Data to Personalized Healthcare: A Patient-Centered Framework, describing the CARE system appears in the Journal of General Internal Medicine.