The era of data-driven R&D is motivating Life Sciences companies to invest in technologies such as machine learning and natural language processing to provide deeper insights into new development strategies. However, many computational approaches struggle to deal with the complexity and variability of unstructured scientific language.
TERMite (TERM identification, tagging & extraction) is at the heart of SciBite’s semantic analytics software suite. Coupled with SciBite’s hand-curated VOCabs, TERMite, can recognise and extract relevant terms found in scientific text.
“Accurate semantic enrichment eliminates ambiguity and transforms unstructured content into rich, machine-readable data.” says James Malone, Chief Technical Officer at SciBite. “With this latest version of TERMite, we are making it even easier for our clients to integrate robust, scalable semantic enrichment capabilities into their business workflows.”
The new version of TERMite introduces:
Read more about TERMite at https://www.scibite.com/platform/termite/
SciBite is an award-winning semantic software company offering an ontology-led approach to transforming unstructured content into machine-readable clean data. Supporting the top 20 pharma with use cases across life sciences, SciBite empowers customers with a suite of fast, flexible, deployable API technologies, making it a critical component in scientific data-led strategies. Headquartered in the UK, we support our global customer base through additional sites in the US and Japan.
SciBite's latest TERMite 6.3 release includes a new set of clinical ontologies as it introduces a set of CDISC vocabularies.Read
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