How to Build a Healthcare Chatbot Assistant using Rasa & Python?

Rise of conversational AI in healthcare through building a chatbot assistant using Rasa and Python is a great way you can provide efficient support for streamlining healthcare processes and engaging patients. Here's a guide that may help create your healthcare assistant chatbot, which can manage anything ranging from appointment scheduling to answering health-related queries and even real-time order tracking for healthcare services.

Why Use Rasa for Health Chatbots?

Rasa is an open source conversational AI framework. It supports NLU and dialogue management, making it the best software to develop strong and flexible chatbots based on healthcare. Custom integration capabilities are also offered, including APIs for appointment booking, healthcare service management, and patient support.

Important Features of a Healthcare Chatbot:

Email Verification: The user is authenticated as a registered patient or has previously been recorded in the database.

Real-Time Tracking of Orders: Users will be able to monitor the care healthcare orders, e.g., medicine deliveries or appointment confirmations.

Queries about Weight Loss Programs: The chatbot will provide information about health care/ wellness programs such as weight loss programs

Q&A Session: Users will be able to pose questions about healthcare and the corresponding response will be retrieved from the database.

WhatsApp Integration: Twilio is used in it, so it's very user-friendly and interactive.

Natural Language Understanding (NLU): It actually allows the Rasa NLU to facilitate comprehension of what the patient wants so as to give this chatbot more conversational responses.

User-Friendly Web Interface: The interface presents the possibilities for a user to easily approach the bot right from one web application.

For deep dive into these features and more, check out the full blog:"How to Create a Healthcare Chatbot Assistant using Rasa & Python".