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Register a new userZero-Shot Clinical Questionnaire Filling From Human-Machine Interactions
صفر لقطة سرية استبيان ملء من التفاعلات البشرية
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في الدراسات السريرية، تستخدم Chatbots MiMicking تفاعلات الطبيب المريض في جمع معلومات حول الحالة الصحية للمريض.في وقت لاحق، يجب معالجتها هذه المعلومات وهيكلية للطبيب.طريقة واحدة لتنظيمها هي تلقائيا ملء الاستبيانات من محادثة الإنسان بوت.من شأنه أن يساعد الطبيب في اكتشاف القضايا المحتملة.نظرا لعدم وجود مجموعة بيانات من هذا القبيل المتاحة لهذه المهمة، فإن مجموعتها مكلفة وحساسة، ونحن نستكشف قدرات نماذج طلقة صفرية للحديث عن الإجابة على السؤال والاستدلال النصي والتصنيف النصي.نحن نقدم تحليلا مفصلا للنتائج واقتراح المزيد من الاتجاهات لملء الاستبيان السريري.
In clinical studies, chatbots mimicking doctor-patient interactions are used for collecting information about the patient's health state. Later, this information needs to be processed and structured for the doctor. One way to organize it is by automatically filling the questionnaires from the human-bot conversation. It would help the doctor to spot the possible issues. Since there is no such dataset available for this task and its collection is costly and sensitive, we explore the capacities of state-of-the-art zero-shot models for question answering, textual inference, and text classification. We provide a detailed analysis of the results and propose further directions for clinical questionnaire filling.
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