1. 筛选到关键基因后对单个关键基因进行多种机器学习的检验，进一步验证筛选到基因的诊断性能。
2. 筛选到的免疫细胞也通过随机森林进行机器学习的检验，进一步验证关键免疫细胞。
3. 最后对关键基因进行分子对接和分子动力学模拟，与药物结合对关键基因进行预测分析。
Characterizing hub biomarkers for post-transplant renal fibrosis and unveiling their immunological functions through RNA sequencing and advanced machine learning techniques