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

Autor: M. Sreeraj, Jestin Joy, Manu Jose, Meenu Varghese, T.J. Rejoice
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 6, Pp 3301-3309 (2022)
Druh dokumentu: article
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2020.08.010
Popis: 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.
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