Chatbot for Cancer Patients
Use Kendra, Lex and Bedrock to chat with the bot about all your cancer related questions
Overview
Conversational Search for Cancer Demo is powered by Amazon Kendra, Amazon Lex and Generative AI. This demo shows a Generative Search and Discovery experience for a user (e.g a patient navigating in the patient portal) to ask specific questions about cancer, treatments, test, procedures, care and maintenance. The solution empowers the patient to ask questions and learn more about specific cancer saving time and effort. This demo can showcase how a Healthcare provider organization can empower their patients using Generative AI based chatbots.
How does it work?
The architecture for this demo is shown below. The solution is based on the QnABot on AWS solution and uses the RAG (Retrieval Augmented Generation) approach for conversational search (QnABot On AWS). This demo uses data from NCI website and indexes the content using Amazon Kendra (NCI). The user interacts with the chatbot using Amazon Lex. The user questions are then sent to Amazon Kendra to find relevant documents that contain the answers. The docuemnts are then sent to the LLM ( Anthropic Claude-v2 in Amazon Bedrock ) to summarize the answer in a human friendly format. The bot is context-aware as it can understand the context of the conversation and respond approriately.
- Note that this demo shows DEBUG and CONTEXT information in the responses. This is optional and can be removed in production.
Customize the demo
This demo is customizable for your customer’s domain/documents. Here are more details on customizing this demo.
Sample questions
- What is Cancer?
- What factors affect it?
- How is it diagnosed?
- How is it treated?
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