Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach
Identification of dysregulated expressed genes As the work flow shown in Fig. S1, three GEO data sets (GSE61145, GSE34198, and GSE66360) were included in this study. A total of 697, 163, and 734 up-regulated and 679, 72, and 741 downregulated genes were obtained in GSE34198, GSE61145, and GSE66360 respectively (Fig. 1A). According to the heatmap shown