# An Integrated Approach to Biomedical Term Identification Systems
## 4 An Architecture for Information Exploration  
In specialized environments like in the biomedical domain, controlled vocabularies are mandatory in order to unify the terminology present in notes, clinical stories, reports and research papers. In Clinical Decision Support (CDS) systems, the precision offered by the a retrieval system to find relevant literature related to a case is paired with a better treatment and clinical intervention [27]. Traditional query-based retrieval engines forces the expert to carefully define the query. As an alternative to that formulation, we propose to initiate the retrieval process by means of a complete text, from which query terms are extracted thanks to a highly performing process of specialized terminology extraction. Besides CDS, clinical research demands for more accurate and agile ways to crawling a growing volume of scientific literature. Our approach proposes an integrated architecture with a core focused on terminology, yet provides continuous feedback and allows interactive retrieval. This architecture is composed of four main components and depicted in Figure 1.  
1. **Terminology knowledge bases**. They are the main source of knowledge in our proposal. Controlled vocabularies are used by this architecture to leverage information retrieval and browsing. These are valuable resources developed intensively across decades in the biomedical domain, and the architecture profits from this polished knowledge to put forward a new framework for digital searches. 2. **The term identification engine**. This is the central part of our system. Starting from any free text, the system identifies the specialized concepts and uses them to retrieve relevant information and to allow semantic exploration on the other two modules considered. 3. **The information retrieval module**. This component retrieves from different sources and collections those documents closer to the concepts identified. These sources can be databases of research papers, articles or even clinical reports. Depending on the orientation of the final system, the architecture would \"plug\" certain databases that the final user is interested in. 4. **Concept exploration**. Semantic links between concepts provided in terminology thesauri and concept graphs, like UMLS, allow for term navigation and gathering. This is an important tool when looking for information, as semantic search is enabled by means of concept exploration wandering the graph of semantic relationships. This tool provides a general overview on the terms of our concern and how they are related. By interacting with the graph of terms, the userwould be able to understand how they are related and discover new terms as potential keywords for enhanced query composition. This work focuses specifically on the search and retrieval of information in order to obtain complete, correct and appropriate answers to the information needs of users. Our approach identifies specialized medical terminology automatically and uses it in a meta-search process. By meta-search we mean that the system uses its own knowledge bases and other search engines showing a combination of the best pages that each one has returned. The knowledge bases semantically enrich the results to obtain a higher precision. Figure 2 shows the operating structure of the system. The system receives an input text and different normalization processes are applied (see Section 4.1) in order to recognize biomedical entities such as diseases, symptoms, treatments, parts of the human body, etc. The system shows the concepts detected along with a list of different ways of writing each concept (synonyms and alternative expressions). Next, using only these concepts, the system searches in several services (see Section 4.3): academic articles in Google Scholar, health information in MedLine and Spanish scientific articles in SciELO. In the last step, the system shows a semantic graph with the relation between these concepts (see Section 4.4).