NLMplus, Semantics for Better Results in Search and Discovery

Reading time: 1 – 2 minutes

WebLib, a small international technology startup of experts in information retrieval, natural language processing and medical informatics, recently released NLMplus, a semantic search and knowledge discovery application that utilizes a variety of semantic resources and natural language processing tools to produce improved search results from the vast collection of biomedical data and services of the National Library of Medicine (NLM).


A common challenge in medical libraries, biomedical research institutions and the healthcare industry is flexible access to heterogeneous databases. NLMplus makes synergistic use of a variety of novel solutions and technologies to maximally utilize NLM’s downloadable data sets, APIs, web services and software tools.

A major innovation of NLMplus is WebLib’s Semantic Search Engine, which typically produces relevant search results with improved precision and recall from 1.6 million PubMed Review articles that are semantically indexed and searched on a WebLib server. The NLMplus application also sends conceptually enhanced Boolean queries to NLM’s PubMed system of more than 21 million citations from the biomedical literature, life science journals, and online books.

Source: PR Web

About the Author

Walter Jessen, Ph.D. is a Data Scientist, Digital Biologist, and Knowledge Engineer. His primary focus is to build and support expert systems, including AI (artificial intelligence) and user-generated platforms, and to identify and develop methods to capture, organize, integrate, and make accessible company knowledge. His research interests include disease biology modeling and biomarker identification. He is also a Principal at Highlight Health Media, which publishes Highlight HEALTH, and lead writer at Highlight HEALTH.