The AI-Powered Hospital Chatbot for Automating Patient Management, Billing, and Lab Results Tracking Using NLP and TensorFlow

Abstract

AI-powered hospital chatbot is an innovative solution designed to streamline hospital operations by automating critical tasks such as patient management, lab result tracking, precautionary guidelines, and billing processes. Developed using Python, the chatbot incorporates Natural Language Processing (NLP) for intuitive user interactions and employs TensorFlow for robust machine learning(ML) capabilities, as explored by Sharma et al. [1] and Singh et al. [4]. For data management, MongoDB ensures efficient handling of patient records, lab reports, and billing information, similar to the methodologies outlined by Kapoor and Shetty [2] and Kumar et al. [3]. By leveraging Google Cloud Platform’s Text-to-Speech technology, the system enhances accessibility and user experience, aligning with findings from Narendran et al. [5].

This intelligent system alleviates the administrative burden on healthcare staff, enabling them to prioritize patient care—a key aspect emphasized in recent studies on AI-powered medical chatbots [7][13]. The chatbot provides real-time access to medical information, ensures accurate record-keeping, and facilitates swift communication between patients and hospital personnel, consistent with the work of Bates [9] and Daher et al. [10]. By improving operational efficiency and patient satisfaction, this AI-driven chatbot marks a transformative advancement in healthcare technology, promoting better resource utilization and delivering quality care more efficiently, as highlighted by Kavyashree and Usha [6] and Zhang and Zheng [11].