The study aims to identify sepsis susceptibility genes in post-surgical patients using an explainable artificial intelligence (XAI) approach applied to GWAS data. A GWAS was performed on 750 postoperative sepsis patients and 3500 population controls. The XAI-GWAS method predicted postoperative sepsis and prioritized SNPs such as rs17653532 and rs15750817475. She discovered risk loci with functions in the regulation of gene expression, DNA replication, cyclic nucleotide signaling, cell proliferation, and cardiac dysfunction. Key genes include PRIM2, SYNPR and RBSN. Preoperative blood tests for these genes could improve risk stratification and early detection. Further research with ethnically diverse cohorts of patients after major surgery is needed to confirm the findings.[7]