Biomedical Abbreviations

Offering a text mining algorithm to detect abbreviations challenge in biomedical texts

Abstract One of the grounds raised in the last few years is the search and extraction of data from biomedical literature. The size and growth of the biomedical literature has created new challenges. Text mining techniques will pave the way to answer this question. Just extracting the definitions for abbreviations and biology is very essential. One of the challenges is a high rate of new abbreviations which introduce, develop and occur in biomedical texts. In this article, we have suggested a combinatorial alignment algorithm to detect abbreviations from biomedical texts. The method is to identify short form and long form pairs where short form of any kind

Because of complexity of the biomedical domain, biomedical sentences are often long[5]. They usually include the words which bode their corresponding semantic types such as : “ Virus in epestein-barr virus” , or “ protein in latent membrane protein“ , or the words which describe characteristics of the referred entities such as: “ Latent in latent membrane protein “. In one time, maybe it is difficult to find describing and short sentences for biomedical concepts like genes and proteins. New abbreviations using the issue are being developed in biomedical text mining[6]. For more comfortable connections, short viewing of biomedical concepts like summery, abbreviations, and signs in context which occurs repeatedly or is hard to describe is being used. Since there are several names and abbreviations in many of biomedical existences, it is so good that an automatic mean facilitates text mining themes for collecting these synonym words and abbreviations. If all the words and abbreviations for one existence could be written as a single sentence in the context, it will be a field work in Information Extraction issue, synonym words of a name decryption of gene and abbreviations of biomedical sentences[7]. Abbreviations and summary usually are used for illnesses and etcetera in biomedical contexts for names of gene. Since the changes of abbreviations-definitions are dependent to the context, they can cause ambiguity[8]. The ability to detect and extract abbreviations and writing them on an optimized definition for data extracting field could be