Information Retrieval System for Medical Narrative Reports (original) (raw)

2004, Lecture Notes in Computer Science

A Comparison of Different Retrieval Strategies Working on Medical Free Texts

J. Univers. Comput. Sci., 2011

Patient information in health care systems mostly consists of textual data, and free text in particular makes up a significant amount of it. Information retrieval systems that concentrate on these text types have to deal with the different challenges these medical free texts pose to achieve an acceptable performance. This paper describes the evaluation of four different types of information retrieval strategies: keyword search, search performed by a medical domain expert, a semantic based information retrieval tool, and a purely statistical information retrieval method. The different methods are evaluated and compared with respect to its appliance in medical health care systems.

Conceptual search in electronic patient record

Studies in health technology and informatics, 2001

Search by content in a large corpus of free texts in the medical domain is, today, only partially solved. The so-called GREP approach (Get Regular Expression and Print), based on highly efficient string matching techniques, is subject to inherent limitations, especially its inability to recognize domain specific knowledge. Such methods oblige the user to formulate his or her query in a logical Boolean style; if this constraint is not fulfilled, the results are poor. The authors present an enhancement to string matching search by the addition of a light conceptual model behind the word lexicon. The new system accepts any sentence as a query and radically improves the quality of results. Efficiency regarding execution time is obtained at the expense of implementing advanced indexing algorithms in a pre-processing phase. The method is described and commented and a brief account of the results illustrates this paper.

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