Frontiers of biomedical text mining: current progress

by: Pierre Zweigenbaum, Dina Demner-Fushman, Hong Yu, Kevin B Cohen

Brief Bioinform (30 October 2007), bbm045.

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Abstract

It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or BioNLP' in general, focusing primarily on papers published within the past year. 10.1093/bib/bbm045

@article{citeulike:1850110, abstract = {It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or BioNLP' in general, focusing primarily on papers published within the past year. 10.1093/bib/bbm045}, author = {Zweigenbaum, Pierre and Demner-Fushman, Dina and Yu, Hong and Cohen, Kevin B. }, citeulike-article-id = {1850110}, doi = {10.1093/bib/bbm045}, journal = {Brief Bioinform}, keywords = {text-classification}, month = {October}, pages = {bbm045+}, posted-at = {2008-01-17 06:31:30}, priority = {2}, title = {Frontiers of biomedical text mining: current progress}, url = {http://dx.doi.org/10.1093/bib/bbm045}, year = {2007} }

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TY - JOUR ID - citeulike:1850110 L3 - citeulike-article-id:1850110 TI - Frontiers of biomedical text mining: current progress JF - Brief Bioinform SP - bbm045 N2 - It is now almost 15 years since the publication of the first paper on text mining in the genomics domain, and decades since the first paper on text mining in the medical domain. Enormous progress has been made in the areas of information retrieval, evaluation methodologies and resource construction. Some problems, such as abbreviation-handling, can essentially be considered solved problems, and others, such as identification of gene mentions in text, seem likely to be solved soon. However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research. In this article we review the current state of the art in biomedical text mining or BioNLP' in general, focusing primarily on papers published within the past year. 10.1093/bib/bbm045 KW - text-classification AU - Zweigenbaum, Pierre AU - Demner-Fushman, Dina AU - Yu, Hong AU - Cohen, Kevin PY - 2007/10/30/ UR - http://dx.doi.org/10.1093/bib/bbm045 ER -

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