Medical documents processing for summary generation and keywords highlighting based on natural language processing and ontology graph descriptor approach

In this paper a new method of data retrieval from free text documents in medical domain is proposed. Presented approach gives the document summary and highlights important keywords in the text to support further analysis of multiple medical documents. The document is processed with natural language processing techniques to find medical keywords and assign them to concepts in the medical ontology. These concepts contribute to higher levels in the hierarchy and build the document descriptor as a graph with concepts in the nodes and corresponding relevance points. The descriptor is used to generate the summary in a form of tree. Finally, we highlight the most important keywords in the original text. Presented experiments demonstrate the proposed approach, which successfully summarizes and highlights meaningful medical information.