Predicting Treatment Outcome from Patient Texts:The Case of Internet-Based Cognitive Behavioural Therapy
Evangelia Gogoulou, Magnus Boman, Fehmi Ben Abdesslem, Nils Hentati Isacsson, Viktor Kaldo, Magnus Sahlgren
Document analysis including Text Categorization and Topic Models Short paper Paper
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Abstract:
We investigate the feasibility of applying standard text categorisation methods to patient text in order to predict treatment outcome in Internet-based cognitive behavioural therapy. The data set is unique in its detail and size for regular care for depression, social anxiety, and panic disorder. Our results indicate that there is a signal in the depression data, albeit a weak one. We also perform terminological and sentiment analysis, which confirm those results.
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