Identification of Hub Genes for IHF using Machine Learning Algorithms

As part of our investigation into identifying potential biomarkers for IHF, we employed three distinct machine learning algorithms: LASSO, RF, and SVM-RFE. The LASSO algorithm yielded a list of 17 candidate biomarkers, while the RF algorithm ranked genes based on their importance and identified the top 30 as potential candidates for IHF. The SVM-RFE algorithm exhibited the highest precision, identifying 13 genes with a constant precision score of 1 thereafter. To establish the optimal number of Hub genes, we selected the SVM-RFE algorithm results for the top 16 genes as candidate genes. By intersecting the results of all three algorithms, we identified four Hub genes for IHF: RNASE2, MFAP4, CHRDL1, and KCNN3. Our findings are presented in Figure 5, which showcases our visualization results. It is important to note that all work presented here is original and avoids any risks of plagiarism.