Mood disorders like depression are common among U.S. adults. Still, such disorders remain challenging for clinicians to diagnose and treat effectively.
A public health researcher at the University at Buffalo is part of a collaborative team of scientists that received a National Science Foundation (NSF) grant to use big data to develop a new approach they say will improve the classification of mood disorders, leading to more effective outcomes for psychiatric patients.
Dr. Rachael Hageman Blair, assistant professor of biostatistics in UB’s School of Public Health and Health Professions, is one of five principal investigators on the one-year, $100,000 planning grant, funded by NSF in a joint effort with the National Institutes of Health. Dr. Hageman Blair’s collaborators on the project include biostatistics, information science, mathematics, biomedical informatics, psychiatry and electrical and computer engineering researchers from the University of Iowa, University of North Carolina-Chapel Hill, University of Oregon and the University of Utah.
Their aim is to use big data to develop a novel methodology and visualization tools to cluster patients with mood disorders. “Existing approaches often break or are inappropriate in big data settings for several reasons,” Dr. Hageman Blair explains. “There is not a one-size-fits-all approach even for well-behaved data sets. Bringing together different methods under a single umbrella with strong visual interpretations holds value for a clinician.”
The collaborators met over the summer at an innovation workshop hosted by the Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation affiliated research institute located in Research Triangle Park, NC. “It was a lot like speed dating for scientists. By the end of the week, I found six great collaborators, and then the work of developing the proposal began,” says Dr. Hageman Blair, who has a PhD in mathematics.
Over the next year, the research team will begin developing their methodology. “We’ll be focusing on applications to mood disorders, which are known to be particularly challenging to classify,” says Dr. Hageman Blair.