Seminars and Events
Unsupervised Machine Learning for Categorizing and Clustering NIH Grants
Event Details
The U.S. National Institutes of Health (NIH) consists of twenty-five Institutes and Centers that award ~80,000 grants each year. The Institutes have distinct missions and research priorities, but there is overlap in these missions and in the types of research they support, which creates a funding landscape that can be difficult for researchers and research policy professionals to navigate. In collaboration with researchers from ISI and other organizations, we have created a publicly accessible database (https://app.nihmaps.org ) in which NIH grants are topic modeled using Latent Dirichlet Allocation, and are clustered using a force-directed algorithm for placing grants as nodes in two dimensional space, where they can be accessed in an online map-like format.