Automatic classification of doctor-patient questions for a virtual patient record query task

Leonardo Campillos Llanos , Sophie Rosset (1) , Pierre Zweigenbaum (1)

1 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur

We present the work-in-progress of automating the classification of doctor-patient questions in the context of a simulated consultation with a virtual patient. We classify questions according to the computational strategy (rule-based or other) needed for looking up data in the clinical record. We compare ‘traditional’ machine learning methods (Gaussian and Multinomial Naive Bayes, and Support Vector Machines) and a neural network classifier (FastText). We obtained the best results with the SVM using semantic annotations, but the neural classifier achieved promising results without it. (Dialogue system, Virtual patient, Machine learning, Neural network classifier)

Mots clés: Dialogue system; Virtual patient; Machine learning; Neural network classifier

Domaines: Informatique [cs]; Informatique et langage [cs.CL]

Leonardo Campillos Llanos, Sophie Rosset, Pierre Zweigenbaum. Automatic classification of doctor-patient questions for a virtual patient record query task. BioNLP Shared-Task Workshop, ACL, Jan 2017, Vancouver, Canada. ⟨hal-01626199⟩