Adaptive neuro-fuzzy inference system for the diagnosis of non-mechanical low back pain.

Back pain is one of the most important causes of disability. Clinical decision support systems (CDSSs) can help physicians diagnose diseases with greater precision. This study designs and implements a CDSS to diagnose non-mechanical low back pain (LBP), including spinal brucellosis, ankylosing spondylitis, spinal tuberculosis, and spinal osteoarthritis using an adaptive neuro-fuzzy inference system (ANFIS). The highest corrected classification percentage was related to spinal brucellosis (82.8%), and CDSS was able to differentiate four non-mechanical LBP types.