Text Mining Applied to Electronic Medical Records: A Literature Review

Text Mining Applied to Electronic Medical Records: A Literature Review

Luís Pereira, Rui Rijo, Catarina Silva, Ricardo Martinho
Copyright: © 2015 |Pages: 18
DOI: 10.4018/IJEHMC.2015070101
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The analysis of medical records is a major challenge, considering they are generally presented in plain text, have a very specific technical vocabulary and are nearly always unstructured. It is an interdisciplinary work that requires knowledge from several fields. The analysis may have several goals, such as assistance on clinical decision, classification of medical procedures, and to support hospital management decisions. This work presents the concepts involved, the relevant existent related work, and the main open issues for future research within the analysis of electronic medical records, using data and text mining techniques. It provides a comprehensive contextualization to all those who wish to perform an analytical work of medical records, enabling the identification of fruitful research fields. With the digitalization of medical records and the large amount of medical data available, this is an area of wide research potential.
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Data Mining Background

Text mining is a variation of data mining (Navathe, B., & Ramez, 2000). Thus, this section introduces the concept of data mining, its conception, techniques, learning methods, and processes that can be used and its automation.

Data mining is the process of understanding and discovering patterns in large data sets to retrieve useful knowledge (Fayyad, Piatetsky-Shapiro, & Smyth, 1996). Regarding healthcare, this knowledge can be useful to improve the quality of treatments, increasing revenues or lower costs of healthcare organization such as a hospital. Data mining is widely used in the fields of computer science, economics, communication and marketing, allowing finding important patterns on information that are, otherwise, difficult to analyse.

It is hard to say when this concept appeared. Data mining use several of Bayes algorithms created in the XVIII century (Pawlak, 2002), but only in 1989-1991 was the term introduced by researcher Gregory Piatetsky-Shapiro (Piatetsky-Shapiro, 1990).

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