In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibus (GEO) analysis combined with a comprehensive database interrogation. Employing a random forest algorithm, we have developed a diagnostic model that demonstrates improved accuracy in distinguishing DUs from normal tissue, with satisfactory results from ROC analysis.
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