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Evaluation of artificial intelligence models for osteoarthritis of the knee using deep learning algorithms for orthopedic radiographs

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World Journal of Orthopedics 2022年第6期13卷 603-614页

作者： Anjali Tiwari murali poduval Vaibhav Bagaria Department of Orthopedics Sir H.N.Reliance Foundation Hospital and Research CentreMumbai 400004India Lifesciences Engineering Tata Consultancy ServicesMumbai 400096India Department of Orthopedics Columbia Asia HospitalMumbai 400004India

BACKGROUND Deep learning,a form of artificial intelligence,has shown promising results for interpreting *** order to develop this niche machine learning(ML)program of interpreting orthopedic radiographs with accuracy,a project named deep learning algorithm for orthopedic radiographs was *** the first phase,the diagnosis of knee osteoarthritis(KOA)as per the standard Kellgren-Lawrence(KL)scale in medical images was conducted using the deep learning algorithm for orthopedic *** To compare efficacy and accuracy of eight different transfer learning deep learning models for detecting the grade of KOA from a radiograph and identify the most appropriate ML-based model for the detecting grade of *** The study was performed on 2068 radiograph exams conducted at the Department of Orthopedic Surgery,Sir HN Reliance Hospital and Research Centre(Mumbai,India)during *** orthopedic surgeons reviewed these independently,graded them for the severity of KOA as per the KL scale and settled disagreement through a consensus *** models,namely ResNet50,VGG-16,InceptionV3,MobilnetV2,EfficientnetB7,DenseNet201,Xception and NasNetMobile,were used to evaluate the efficacy of ML in accurately classifying radiographs for KOA as per the KL *** of the 2068 images,70%were used initially to train the model,10%were used subsequently to test the model,and 20%were used finally to determine the accuracy of and validate each *** idea behind transfer learning for KOA grade image classification is that if the existing models are already trained on a large and general dataset,these models will effectively serve as generic models to fulfill the study’s ***,in order to benchmark the efficacy,the results of the models were also compared to a first-year orthopedic trainee who independently classified these models according to the KL *** Our network yielded an overall high accuracy for detecting KOA,ranging from 5

关键词： Osteoarthritis Artificial intelligence Knee Computer vision Machine leaning Deep learning

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