The application of deep learning methods in knee joint sports injury diseases

ABSTRACT

Deep learning is a powerful branch of machine learning, which presents a promising new approach for diagnose diseases. However, the deep learning for detecting anterior cruciate ligament still limits to the evaluation of whether there are injuries. The accuracy of the deep learning model is not high, and the parameters are complex. In this study, we have developed a deep learning model based on ResNet-18 to detect ACL conditions. The results suggest that there is no significant difference between our proposed model and two orthopaedic surgeons and radiologists in diagnosing ACL conditions.

KEYWORDS:

• Deep-learning
• machine-learning
• automated model
• anterior cruciate ligament

Disclosure statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Data availability statement

This study used a MRNet dataset that gathered from Stanford University Medical Center. This dataset available online and anyone can be used.