Leveraging Computerised Automation for Long-Term Monitoring of Total Hip Replacements

Abstract

Total Hip Replacement (THR) has significantly improved patients' mobility and quality of life by alleviating hip pain. However, long-term implant success is influenced by various factors that may lead to joint instability or failure. Early detection of such issues is crucial for effective patient care and intervention.

This study explores the application of image recognition algorithms for analysing radiographs to accurately assess joint stability in individuals who have undergone THR. By leveraging advanced image processing techniques, this approach enables continuous monitoring of implant integrity. Despite improvements in healthcare access, patient attrition after two years remains a challenge. The integration of Computerised Automated Machines (CAMs) can enhance patient screening, efficiently identifying those in need of further medical evaluation. By combining automation with precise diagnostic capabilities, CAM technology presents a promising solution for optimising post-THR assessments, streamlining healthcare operations, and improving long-term patient outcomes.