A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

« The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousands of articles for new information about modelled entities is a painstaking and low-reward task. Text mining can be used to help a curator extract relevant information from this literature in a systematic way. We propose the application of text mining methods for the neuroscience literature. (…) »

Source > link.springer.com, Shardlow, M., Ju, M., Li, M. et al., Neuroinform (2018). https://doi.org/10.1007/s12021-018-9404-y