A Role of Machine Learning and Deep Learning Techniques for Preoperative Prediction in Shoulder Arthroplasty: Survey

Abstract

In the last few years, rapid acceptance and improvement of technology have been seen in shoulder arthroplasty practices. The success rate of shoulder arthroplasty can be improved by taking advantages of artificial intelligence for finding preoperative parameters and better decision-making. The primary identification and the selection of which sort of arthroplasty is employed have relied on the indications like inflammatory arthritis and humerus fractures. Different artificial intelligence techniques used and their impact on the prediction of shoulder arthroplasty are discussed in our paper. We review the artificial intelligence-based techniques in terms of speculative and investigational work carried out in the literature.