ORTHOPEDIC PATIENTS ANALYSIS USING CNN

  • Tatikonda Gayathri, V. Nagi Reddy, K.Sushma, Kalluri Sivakrishna
Keywords: (k-Nearest Neighbor,CredulousBayes,Random Forest Classifier)

Abstract

The muscular sicknesses are getting gigantic step by step. Plate Hernia and Spondylolisthesis are two normal muscular sicknesses. The use of AI in the clinical field is the moving methodology for early forecast and cure of sicknesses. The developing number of muscular infection has lead individuals to endure at an early age and it very well may be forestalled through an early finding. Subsequently, this examination seeks to assist the clinical experts with anticipating muscular sickness early and group them as needs be. For this reason, five AI calculations, for example, k-Nearest Neighbor, uphold vector machine, credulous Bayes, choice tree and Random Forest Classifier, have been applied to a dataset of 310 patients containing six biomechanical highlights that portray the condition of the patients' pelvic and timber. The calculation results are then analyzed and the one that gave the best outcome a precision in the middle of 78 % to 84 %.

Published
2021-07-11
How to Cite
K.Sushma, Kalluri Sivakrishna, T. G. V. N. R. (2021). ORTHOPEDIC PATIENTS ANALYSIS USING CNN. Design Engineering, 2571- 2579. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/2647
Section
Articles