Abstract:Motivation:The rapidly increasing size of biomedical databases such as MEDLINE requires the use of intelligent data mining methods for information extraction and summarization. Existing biomedical text-mining tools have limited capabilities for inferring topological and network relationships between biomedical terms. Very often too much is returned during summarization leading to information overload. Results: We present herein SEACOIN 2.0, an interactive knowledge discovery and hypothesis generation tool for … Show more
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