Extraction of Lifestyle Habits Described in Blogs of Diabetics

DOI

Bibliographic Information

Other Title
  • 糖尿病患者のブログに記述された生活習慣の抽出

Abstract

<p>Tackling diabetes, an increasingly common lifestyle-related illness, requires information on patients’ lifestyle and habits. Blogs maintained by patients afflicted with the incurable illness may be useful for analyzing how lifestyle affects health-status. In this paper, we propose an intrinsic expression extractor that extracts keywords related to lifestyle and health-status from blogs of patients diagnosed with type-2 diabetes. To counter class imbalance and add to the corpus, the proposed method tags each keyword with information based on cue-words extracted from manually tagged data. The named-entity recognition (NER) for the extracted keywords uses a bidirectional gated recurrent unit neural network (BiGRU) and was evaluated for accuracy by cross-validation. We obtained F1-score of approximately 0.76. Although the accuracy of extraction can further be improved, the novel approach has applications in analyzing and improving the lifestyle of diabetes-afflicted patients.</p>

Journal

Keywords

Details

  • CRID
    1390293633437552768
  • DOI
    10.1541/ieejeiss.142.1144
  • ISSN
    13488155
    03854221
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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