Pain Screening in Orthopedics Using Machine Learning

In this study, we focus on a diagnostic system for the field of orthopedic surgery that classifies patients' pain with high accuracy. The proposed system uses machine learning on questionnaire response data to determine pain and incorporates questionnaire items in addition to the traditional ones. Traditionally, the screening of neuropathic pain using existing methods has yielded diagnostic accuracy rates of 10 - 20%. However, our proposed approach achieves an 80% accuracy rate based on empirical data.