In the hypercompetitive Life Sciences industry, organizations are faced with ever-increasing volumes of information. To speed decision-making, increase efficiency and reduce costs they must be able to quickly gain actionable insight from their data.
Vocabularies and natural language processing (NLP) often work hand-in-hand to provide text analytics solutions. Yet in the field of Biomedicine, standard NLP algorithms can be challenged by the specialized terminology. Biomedical vocabularies and ontologies are the keys to ensure the text is accurately analyzed.
Hear Jon Stevens, NLP Software Developer at AbbVie and Jim Morris, Senior Information Scientist at Semaphore discuss how the use of domain-specific vocabularies/ontologies and Semantic NLP engines can learn from each other to deliver better text analytics solutions.
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