NLM DIR Seminar Schedule

Abstract:

Searching and reading relevant literature is a routine practice in biomedical research. However, it is challenging for a user to design optimal search queries using all the keywords related to a given topic. Hence, we developed LitSuggest, a web server that provides an all-in-one literature recommendation and curation service to help biomedical researchers stay up to date with scientific literature. LitSuggest combines advanced machine learning techniques for suggesting relevant PubMed articles with high accuracy, and allows users to curate, organize, download, and share classification results in a single interface, enabling collaborative analysis and curation of scientific literature. Literature access is further improved by the development of specialized search engines such as LitVar2, allowing users to conduct semantic search beyond keywords and to quickly find literature related to their variant of interest.