Modeling Just the Important and Relevant Concepts in Medicine for Medical Language Understanding: A Survey of the Issues

Over the past two decades, two challenging, ongoing domains of medical informatics research have been the construction of models for medical concept representation and the inter-related task of understanding the deep meaning of medical free texts. These domains can take advantage of each other by exploiting the rich semantic content embedded in both concept models and medical texts. This review highlights how these two inter-related domains have evolved by focusing on a number of significant works in this area. The discussion examines one particular aspect: how to employ medical modeling for the purpose of medical language understanding. The understanding process analyzes and extracts the content of medical free texts, and stores the information in a deep semantic representation, useful for future elaborated semantic-driven information retrievals. It is now recognized in the medical informatics community that such understanding processes can be augmented through use of a domain-specific knowledge base that describes what can actually occur in a given domain. For this, a well-balanced representation schema should be developed somewhere between a partial but accurate, versus a complete but complex semantic representation. These observations are illustrated using examples from two major independent efforts undertaken by the authors: the elaboration and the subsequent adjustment of the RECIT multilingual analyzer to a solid model of medical concepts, and the recasting of a frame-based interlingua system, originally developed to map equivalent concepts between controlled clinical vocabularies.