Searching for information and the extraction of concepts from full text in natural language is rapidly becoming ever more important in the healthcare and the pharmaceutical industries. Rapid access to information in a pre-configured format is the key concept. The amount of data is too vast for manual access to particular information. With the US government increasing the reporting requirements daily, healthcare providers need an accurate, efficient and affordable solution to identify, validate, capture, and share clinical information, they need MedLEE™!
MedLEE™ Natural Language Processing can semantically search, index and extract all of the relevant information from medical documents, which provides quick access to a very large amount of data in a computer readable format. The MedLEE™ NLP output can be used for semantic search and retrieval, document classification, information extraction to populate EMR's, data mining, code extraction, core measures, PQRI, Infection Surveillance, Patient summary data, clinical trial (inclusion/exclusion screening), drug discovery and much more.
The MedLEE™ NLP engine utilizes a deep syntactical parsing technology that gives the engine superior ability to assess negation, uncertainty and verb tenses in narratives. The underlying MedLEE™ engine is used for disambiguating terms, and mapping them into a broader conceptual framework, where they can be directly mapped to standard terminologies or proprietary systems. Natural language processing allows the transformation of unstructured data into formally represented data.
MedLEE™ provides a unique solution for knowledge management that enables healthcare providers to meet the meaningful data use standards today.
