Data analytics provider Atigeo has launched xPatterns Explorer into the U.S. National Institutes of Health's PubMed body of medical research.
PubMed’s library of more than 400,000 individual documents and unstructured data provides the foundation for nearly all U.S. medical research. However, deriving meaning from this massive data warehouse is notoriously difficult, as PubMed’s search function is outdated and linear, according to a release.
The new data analytics tool from Bellevue, Wash.-based Atigeo explores PubMed's mass of data. Explorer is powered by the company's xPatterns semantic search platform and discovers relevant concepts and documents relating to an original Pubmed search query and fine tunes its search results over time through machine learning of a user's interaction with the documents, according to the release.
xPatterns is designed to solve the unstructured data relevance problem, applying analytics to large sets of unstructured text documents (such as PubMed) by assigning relevance scores and generating domain concepts. Users can submit search queries to find relevant documents organized into clusters. The xPatterns platform is both linguistically and data agnostic.