The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is diagnosis of the spondylolisthesis using biomedical data that is derived from the shape and orientation of the pelvis and lumbar spine. The data set has six attributes including pelvic incidence, pelvic tilt, lumbar lordosis angle, sacral slope, pelvic radius and grade of spondylolisthesis and two class including normal and abnormal. From UCI machine learning repository, 100 normal and 150 spondylolisthesis patient’s data used for this study. Mahalanobis Taguchi System(MTS) application process and the diagnosis results described in this paper.

Abstract
 1. 서론
 2. Mahalanobis Taguchi System
 3. MTS를 이용한 척추 전방 전위증(Spondylolisthesis)의 진단
  3-1. 변수 데이터
  3-2. MTS기법의 전개
  3-3. 유효 변수의 선정
 4.. 결론
 참고문헌

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