DISQOVER’s NLP technology comes with a powerful named entity recognition (NER) and an extraction engine which allows you to quickly find and analyze information about specific biological entities and their relationships (such as diseases, genes, proteins, and more), populations, interventions, and outcomes that are mentioned in large volumes of text data.
The NLP enhancement for public data uses two models:
Often, the publicly available clinical studies do not specifically annotate patient demographic, intervention, outcome, or biomarker information in a structured way, meaning important knowledge or studies may be missed. Through NLP, DISQOVER can reach this siloed knowledge, add it to the knowledge graph and make it available for search and exploration.
Find more hidden information inside your own, private data.
The NLP functionality for private data comes with the following three models: