Gender-enriched syntactic pattern features from Twitter data recognize bipolar disorder with F1 scores above 91%, outperforming TF-IDF, LIWC, ELMO, and BERT baselines.
The lancet 370, 9590 (2007), 859–877
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Leveraging Linguistic Characteristics for Bipolar Disorder Recognition with Gender Differences
Gender-enriched syntactic pattern features from Twitter data recognize bipolar disorder with F1 scores above 91%, outperforming TF-IDF, LIWC, ELMO, and BERT baselines.