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Nanomedicine Entity Extraction

There is a critical need to automatically extract and synthesize knowledge and trends in nanotechnology research from an exponentially increasing body of literature. Engineered nanomaterials (ENMs), such as nanomedicines, are continuously being discovered and Natural Language Processing approaches can semi‐automate the cataloging of ENMs and their unique physico‐chemical properties; automatically aggregate studies on their exposure and hazards; and link the physicochemical properties to the measured effects.. The goal of this project is to develop a nanomedicine entity extraction system to automatically identify nanomedicine physico-characteristics, exposure and biological effects.