{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automatic-classification-of-doctor-patient","title":"Automatic classification of doctor-patient questions for a virtual patient record query task","arxiv_id":null,"date":"2017-08-01","proceeding":"WS 2017 8","authors":["Leonardo Campillos Llanos","Sophie Rosset","Pierre Zweigenbaum"],"abstract":"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, whereas the neural classifier achieved promising results without it.","url_abs":"https://aclanthology.org/W17-2343","url_pdf":"https://aclanthology.org/W17-2343.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"dialogue-management","task_name":"Dialogue Management"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"named-entity-recognition-ner","task_name":"Named Entity Recognition (NER)"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[{"method_slug":"svm","method_name":"SVM"}],"datasets_introduced":[{"slug":"doctor-patient-questions-french","name":"Doctor-patient questions (French)","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}