Comparative analysis of Machine Learning approaches for early stage Cervical Spondylosis detection

Cervical Spondylosis (CS) is a chronic spinal condition in which the spine gradually stiffens and can finally become completely inflexible. It is arduous to diagnose in early stages and leads to delay in medication. The risk level of Cervical Spondylosis can be reduced if it is detected in primary care. Based on this objective, a system is designed and developed to diagnose and predict the severity of cervical spondylosis in early stages. Different machine learning techniques are evaluated for this and results indicate that machine learning techniques can provide a low cost and accurate mechanism for early stage spondylosis detection. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of King Saud University.

Automated summary

Cervical Spondylosis is a chronic spinal condition that can be difficult to diagnose in early stages, but primary care detection can reduce the risk. Machine learning techniques can provide a low-cost, accurate mechanism for early stage spondylosis detection.