Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning

Figure 3

A machine learning-based gene screening process. (a) The random forest model of GHR prediction shows the importance of GHR-related 23 m6A enzymes. The genes are sorted by importance, and the m6A types to which they belong are shown in the legend. (b) SVM-RFE-based GHR prediction model for gene screening process. The final model accuracy was highest when five m6A regulatory genes were screened out. (c) ROC curves of SVM models constructed based on the screened five genes. (d) The variable selection process of the NPR3 prediction model based on SVM-RFE showed the highest model prediction accuracy when 21 genes were included. Abbreviations: ROC: receiver operating characteristics; SVM-RFE: support vector machine-recursive feature elimination.

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