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The purpose of this study is to extract features and structure them using text mining and to analyze changes over time on consultation records accumulated in a cancer consultation and support center database from 2009 to 2018. The text-mining approach worked effectively under conditions of expanding data, and a co-occurrence network revealed patterns and trends in the content of consultations.
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