نحن نركز على نماذج الحوار في سياق الدراسات السريرية حيث الهدف هو المساعدة في جمع، بالإضافة إلى المعلومات الوثيقة التي تم جمعها بناء على استبيان معلومات صريحة ذات صلة طبيا.لتعزيز مشاركة المستخدم وعنوان هذا الهدف المزدوج (جمع مجموعة من نقاط البيانات المحددة مسبقا ومعلومات غير رسمية حول حالة المرضى)، نقدم نموذج فرعي مصنوع من ثلاثة برادات: قائمة على المهام ومتابعة وبوت اجتماعي.نقدم طريقة عامة لتطوير روبوتات المتابعة.نحن نقارن تكوينات الفرقة المختلفة ونؤثر أن مزيج من الروبوتات الثلاثة (I) يوفر أساسا أفضل لجمع المعلومات من مجرد المعلومات التي تبحث عن الروبوت و (2) بجمع المعلومات بطريقة أكثر سهولة الاستخدام بطريقة أكثر فاعلية بحيث تكون فرقةنموذج يجمع بين المعلومات التي تبحث عنها والروبوت الاجتماعي.
We focus on dialog models in the context of clinical studies where the goal is to help gather, in addition to the close information collected based on a questionnaire, serendipitous information that is medically relevant. To promote user engagement and address this dual goal (collecting both a predefined set of data points and more informal information about the state of the patients), we introduce an ensemble model made of three bots: a task-based, a follow-up and a social bot. We introduce a generic method for developing follow-up bots. We compare different ensemble configurations and we show that the combination of the three bots (i) provides a better basis for collecting information than just the information seeking bot and (ii) collects information in a more user-friendly, more efficient manner that an ensemble model combining the information seeking and the social bot.
References used
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