Design an artificial intelligence chatbot to support patient declaration and direction of examination rooms for outpatients

다국어 초록 (Multilingual Abstract)

Background/Objectives: Automation is a trend currently, and chatbots are an excellent way for organizations to automate customer service duties. The medical profession has been put under immense strain during COVID-19 outbreaks as the number of patients increases rapidly, causing medical institutions and hospitals to be overcrowded. Users will find it challenging to schedule an appointment at a clinic, provide health advice, or update information due to this. Methods/Statistical analysis: A chatbot that supports users in advising, making appointments, and screening COVID-19 patients at clinics can be a valuable resource for both the user and the clinic in this situation. This paper developed a framework for developing a chatbot for clinics using a specific Frequent Answer Question (FAQ) dataset relating to COVID-19 and frequent diseases in Vietnam. In our study, the RASA framework was used with data collected from interviewing receptionists and website of clinics. Findings: Our chatbot can act as a counsellor, assisting patients with scheduling appointments, answering inquiries about symptoms of common illnesses, in particular, COVID-19 patient screening. In addition, we integrated our chatbot with Facebook Messenger and Zalo, two major social networking sites in Vietnam. Improvements/Applications: For specific implementation with each clinic, dataset enhancement and new services information update are necessary for broader applications.

목차 (Table of Contents)

• Abstract
• I. INTRODUCTION
• II. RELATED WORKS
• A. Chatbot
• B. Medical and healthcare industry
• C. RASA framework
• III. RESEARCH METHOD
• A. Creating chatbot’s process
• B. Experiments
• C. Discussion
• IV. CHATBOT IMPLEMENTATION
• V. CONCLUSION
• REFERENCES