Figure classification in biomedical literature to elucidate disease mechanisms, based on pathways

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ObjectiveAs more full-text biomedical papers are becoming available in digitized form online, there is a need for tools to mine information from all parts of such papers. Because the figures and legends/captions in biomedical papers provide important information about research outcomes, mining techniques targeting them have attracted a great deal of attention. In this study, we focused on pathway figures that illustrate signaling or metabolic pathways, because many of these are important in understanding disease mechanism(s). We developed a figure classification system based on textual information contained in biomedical papers to provide an automated acquisition system for such pathway figures.

论文关键词:Figure classification,Text mining,Supervised machine learning,Disease-related pathways,Multi-factorial disorders

论文评审过程:Received 15 March 2009, Revised 26 March 2010, Accepted 29 March 2010, Available online 27 April 2010.

论文官网地址:https://doi.org/10.1016/j.artmed.2010.04.005