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

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].

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-12
DOI
https://doi.org/10.52783/jisem.v10i34s.5785
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Kalyan Babu Allamudi
Journal of Information Systems Engineering & Management
Artificial Intelligence in Healthcare
article

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

Kalyan Babu Allamudi
article en

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].

Journal of Information Systems Engineering & ManagementVol. 10(34s)
Openalex Percentile: Top 92%
Artificial Intelligence in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.