Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification

Tittaya Mairittha, Tsuyoshi Okita, Sozo Inoue,
Ubicomp Workshop on Computing For Well-being (WellComp)
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Telemedicine is an emerging challenge for the shortage of qualified professionals, particularly in under-resourced re- gions. Physical assessment by a non-medical doctor is a practice in telemedicine which discovers essential symp- tom of a patient who needs to consult a doctor. We aim at facilitating this stage with a conversational chatbot which identifies the patient by conversation. Adopting the proce- dures of physical assessment one critical types of conver- sation involves in the self-diagnosis. Further, it turned out that useful kinds of questions in chatbot at this stage are related to Yes/No questions. We discovered that particular difficulties lie in the ambiguous replies by the patients: a patient modifies a question which makes them answer yes or no, a response does not the corresponding reply to the question, a reply involves some part yes and some part no, and so on. Focusing on this particular type of question we introduce a text classifier using Long Short-Term Memory (LSTM) and build a corpus using Twitter.

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