Machine Learning Algorithm for Knee Arthroplasty Loosening Detection

Overview

Department of Orthopaedics and Traumatology at the Chinese University of Hong Kong developed an images-based machine learning algorithm that allows detection of knee arthroplasty loosening with high accuracy and predictability.

  • Machine Learning Algorithm for Knee Arthroplasty Loosening Detection 0
  • Machine Learning Algorithm for Knee Arthroplasty Loosening Detection 1
Technical name of innovation
Knee Arthroplasty Loosening Automatic Detection System
Research completion
2023
Problem addressed

Detection of loosening with high sensitivity, which facilitate early detection of loosening, thus allow prompt intervention to help prevent further damage and improve patient outcome.

Innovation
  • By uploading an X-ray image, the detection will then demonstated
  • Heat map will also generate to locate which area most likely to occur loosening
Key impact
  • Accurate quantification of the level of loosening can help clinicians make better decisions about whether to revise an implant or continue monitoring.
  • Reduce burden on healthcare systems and workloads for surgeons
Award
  • Bronze medal at the “2023 Geneva International Exhibition of Inventions”
Application
  • Different Hospital

Patent

  • Publication No.: CN 114694790
The Chinese University of Hong Kong (CUHK)

Founded in 1963, The Chinese University of Hong Kong (CUHK) is a forward-looking comprehensive research university with a global vision and a mission to combine tradition with modernity, and to bring together China and the West. CUHK teachers and students hail from all around the world. Four Nobel laureates are associated with the university, and it is the only tertiary institution in Hong Kong with recipients of the Nobel Prize, Turing Award, Fields Medal and Veblen Prize sitting as faculty in residence. CUHK graduates are connected worldwide through an extensive alumni network. CUHK undertakes a wide range of research programmes in many subject areas, and strives to provide scope for all academic staff to undertake consultancy and collaborative projects with industry. 

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