Effect evaluation of rheumatoid arthritis early diagnosis model based on support vector machine
HE Jiao
JIA Zhi-lin
Abstract：Objective To establish an early diagnosis of rheumatoid arthritis based on support bector machine and e -valuate its predictive effect .Methods Included 240 rheumatoid arthritis patients and 180 other rheumatic autoimmune disease patients , anti-CCP and RF was measured .Establish an early diagnosis of rheumatoid arthritis based on support vec-tor machine , and evaluate its predictive effect by using 5-fold cross validation .Results The correct diagnostic rate of 5-fold cross validation was 85.48%, diagnostic sensitivity was 88.33% and diagnostic specificity was 81.67%, prediction diagnostic accuracy was better than RF and anti-CCP (all P<0.01).MMC was 0.702 65.Conclusion The study sug-gests that rheumatoid arthritis early diagnosis model based on support vector machine have a prediction diagnostic accuracy .
Keywords：rheumatoid arthritissupport vector machinediagnostic modelanti-CCPrheumatoid factor
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：3( 18-20 )