Enhancing Healthcare Management: A Case Study of a Medical Chatbot in Egypt | ||||
| Benha Journal of Applied Sciences | ||||
| Article 21, Volume 9, Issue 5, May 2024, Page 199-210 PDF (602.65 K) | ||||
| Document Type: Original Research Papers | ||||
| DOI: 10.21608/bjas.2024.317337.1499 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
shimaa Ismail Mustafa   1; Lina Ayman Salem2; Tarek Shishtawy3; Noha El-Attar3
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| 1Information Systems Department, faculty of computers and Artificial Intelligence | ||||
| 2Information Systems Department, Faculty of Computers and Artificial Intelligence, Benha University | ||||
| 3Information Systems Department, Faculty of computers and Artificial Intelligence, Benha University | ||||
| Abstract | ||||
| In hospitals, receptionists are generally responsible for the following functions: greeting and answering inquiries from visitors, providing them with the appropriate information, and ensuring that hospital staff and patients receive timely and professional communication. This paper presents the implementation and deployment of a medical chatbot designed to replace the traditional receptionist role in hospitals where their visitors speak Arabic. The proposed case study here is an Egyptian hospital. The user can ask questions in text and the answers can be text or voice. The presented chatbot utilizes the power of GPT-4, which represents one of the most powerful large language models (LLMs) available to generate text. This model is merged with prompt engineering capabilities for fine-tuning specific tasks or instructions. This merger has gained traction to enhance model performance and adaptability. The model is integrated with an SQLite database to provide immediate information to patients about doctor availability, examination costs, hospital policies, and more. The chatbot demonstrates a significant potential to streamline hospital operations, improve patient satisfaction, and reduce administrative workload. The evaluation shows a 99% accuracy rate, indicating the high reliability of the system. | ||||
| Keywords | ||||
| GPT-4; Question Answering Bot; Automatic Hospital Receptionist; Prompt Engineering | ||||
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