Email Print Share
November 23, 2015

Big Data to individualize management of chronic diseases


Some chronic conditions, such as the autoimmune disease scleroderma, are especially difficult to treat because patients exhibit highly variable symptoms, complications and treatment responses. The process of finding an effective treatment for an individual can be frustrating for doctors, and painful and expensive for patients. With support from the National Science Foundation (NSF), computer scientist and professor Suchi Saria, with Dr. Fredrick Wigley and an interdisciplinary team of experts at Johns Hopkins University, is leading a groundbreaking effort using Big Data to ease some of that pain for scleroderma patients. The team's research is in machine learning, a subfield of computer science and statistics that allows machines to learn from data. The team designs statistical algorithms that enable computers to analyze large volumes of medical records and identify subgroups of patients with similar patterns of disease progression.

Credit: National Science Foundation


Images and other media in the National Science Foundation Multimedia Gallery are available for use in print and electronic material by NSF employees, members of the media, university staff, teachers and the general public. All media in the gallery are intended for personal, educational and nonprofit/non-commercial use only.

Videos credited to the National Science Foundation, an agency of the U.S. Government, may be distributed freely. However, some materials within the videos may be copyrighted. If you would like to use portions of NSF-produced programs in another product, please contact the Video Team in the Office of Legislative and Public Affairs at the National Science Foundation.

Additional information about general usage can be found in Conditions.