Importance of Artificial Intelligence-based Radiography in the Examination and Treatment of Patients with Subacromial Impingement Syndrome

Abstract

According to various estimates, shoulder pain covers 7-26% of all diseases faced by the global population. In addition, according to studies by Scandinavian scientists, up to 18% of the population's loss of working capacity and paid sick leave are caused by shoulder pain. According to experts, the number of these diseases is already approaching epidemic levels in Sweden, Finland, Japan, and the United States. Insurance payments for diseases caused by shoulder pain are second only to vertebrogenic pain. Subacromial impingement syndrome is the main cause of this pain. Diagnosis includes a complex of clinical and instrumental research methods. A reliable diagnosis of the presence of subacromial impingement syndrome, as well as the type, nature, and severity of subacromial muscle compression, is achieved using modern methods for visualizing the internal structures of the shoulder. It should be noted that radiography and ultrasound are important among them. To determine the model performance of artificial intelligence in detecting rotator cuff pathology using different imaging modalities and to compare its capability with that of physicians in clinical scenarios. Neck-shoulder syndrome is one of the most frequent causes of disability in the population, accounting for 18% of disability sheets. The treatment of pathologies attracts physicians of various specialties: orthopedic traumatologists, neurosurgeons, anesthesiologists, resuscitators, surgeons, neurologists, therapists, physiotherapists, and physical therapy physicians.