Next Generation AI-Enhanced Intelligent Imaging for Automated Knee X-ray Interpretation in Osteoarthritis: Front office Integration and Employee Training

Abstract

Osteoarthritis is a long-lasting musculoskeletal ailment in which the degenerative alterations in the cartilage of the articles progressively arise. As the pathological anatomy develops to bone structure degeneration, it results in pain, stiffness and functional impairment. It results in immobility, reduced quality of life, more susceptibility to fractures, hospitalization, and mental health problems in the older adults and postmenopausal women. To address the increasing global prevalence of OA and the necessity to diagnose X-rays of the knee promptly, affordably and accessibly, this paper presents an AI-based imaging system based on the use of Convolutional Neural Networks (CNNs) and compares their results with the existing machine learning models. The framework will be structured to integrate the front-office workflows and streamline the diagnostic process of patient registration to report delivery and establish a well-organized staff training ecosystem aimed at enabling clinical staff to operate the AI-enabled workflow and adapt to it. The study offers a comprehensive, deployment ready, diagnostic platform through advanced automation, user oriented front-office functionality and the consistent upskilling of the workforce, to provide scalable, precise, cost effective OA detection, clinical efficiency, interpretative variability reduction, and workforce transition to scalable intelligent, patient centred care.

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