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The increasing demand for efficient healthcare services has encouraged the
integration of intelligent technologies to assist medical diagnosis and hospital
management. This paper presents an AI-Based Fracture Detection and Smart
Hospital Queue Management System, developed using Python and image
processing techniques. The system aims to assist in detecting bone fractures from
X-ray images while improving hospital queue efficiency.
The fracture detection module uses grayscale conversion, edge detection, and
contour analysis to identify fracture patterns. Based on these patterns, the system
calculates fracture severity and estimates recovery time. The queue management
module generates tokens, maintains real-time status, and notifies patients.
The system is implemented using Streamlit, providing an interactive interface.
Results show improved efficiency in both diagnosis support and patient
management. This system demonstrates how AI and automation can enhance
healthcare services.
"Smart Fracture Detection and AI Hospital Queue Management Sytem", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c232-c241, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604301.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator