Web-based chatbot for Frequently Asked Queries (FAQ) in Hospitals.

Area of Science:

• Health Informatics
• Artificial Intelligence in Healthcare

Background:

• Current local hospital systems lack transparent and reliable online data access for user queries.
• Patients often act as passive communication channels, highlighting a need for improved interaction methods.

Purpose of the Study:

• To develop an intelligent web chatbot framework for managing user requests and providing efficient access to local hospital information.
• To enhance communication channels between users and hospital staff.

Main Methods:

• Integration of a chatbot engine using machine learning (ML) approaches, including gradient descent (GD).
• Application of natural language processing (NLP) algorithms for text processing and data extraction.
• Sequential application of GD on mini-batches of trained data.

Main Results:

• Successful incorporation of ML algorithms for managing synchronized text and voice messages.
• Demonstrated capability of the chatbot in handling user requests and providing information.

Conclusions:

• The developed chatbot offers a superior solution for data extraction from local hospitals.
• The chatbot functions as an effective communication channel, reducing crowds and improving user and staff experience.