Abstract
With an ever growing number of published scientific studies, there is a need for automated search methods, able to collect and extract as much information as possible from those articles. We propose a framework for the extraction and characterization of brain activity areas published in neuroscientific reports, as well as a suitable clustering strategy of said areas. We further show that it is possible to obtain three-dimensional summarizing brain maps, accounting for a particular topic within those studies. After, using the text information from the articles, we characterize such maps. As an illustrative experiment, we demonstrate the proposed mining approach in fMRI reports of default mode networks. The proposed method hints at the possibility of searching for both visual and textual keywords in neuro atlases.
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Gonçalves, N., Oja, E., Vigário, R. (2014). Medical Document Mining Combining Image Exploration and Text Characterization. In: Džeroski, S., Panov, P., Kocev, D., Todorovski, L. (eds) Discovery Science. DS 2014. Lecture Notes in Computer Science(), vol 8777. Springer, Cham. https://doi.org/10.1007/978-3-319-11812-3_9
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DOI: https://doi.org/10.1007/978-3-319-11812-3_9
Publisher Name: Springer, Cham
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