Artificial Intelligence Healthcare Chatbot System using Deep Learning Amazon SageMaker with Deployment using Large Language Model

The use of artificial intelligence (AI) in the healthcare sector has resulted in the creation of sophisticated systems that could improve patient care and medical decision-making. This paper introduces the design and implementation of an AI-based healthcare chatbot system with deep learning techniques and large language models (LLMs) for better medical diagnosis and patient interaction. The proposed system incorporates Amazon SageMaker for deployment and incorporates few-shot learning, transformers, and medical knowledge graphs to enhance the accuracy and responsiveness of the chatbot. The system is made to assist healthcare providers and patients both by delivering correct medical information, disease diagnosis, and real-time support in medical queries. The most recent advancements in medical concept normalization and NLP are merged to enable the chatbot to easily comprehend and process sophisticated medical text. The paper also tackles the most immediate challenges in front of it, such as coming up with a user interface and ethical considerations of physician-patient power imbalance on online healthcare websites. The work contributes to the emerging body of work on AI-driven health care applications, bringing attention to the promise of conversational AI for better healthcare delivery.