IOMED accellerates research operations through the re-use of data contained in structured and unstructured clinical records.
IOMED developed a Natural Language Processing (NLP) engine that identifies and extracts clinically relevant concepts within medical records, which are not structured (ie: they are in plain, "normal" language). We transform this information into a structured, standardized and interoperable database, which contains the complete clinical information from the original text. Specifically, our tool extracts and encodes relevant medical concepts like symptoms and diseases, taking into account their context. This allows to perform patient screening using hundreds of variables, massively increasing recruitment speed and size.