Head and neck squamous cell carcinomas（HNSCC）rank as the sixth most common cancer globally，with early diagnosis challenging due to subtle symptoms and the absence of specific biomarkers. With the development of liquid biopsy technology， circulating free DNA（cfDNA），as its core test object，has the advantages of non -invasive，dynamic monitoring and reflecting tumor characteristics，and shows promising applications in early screening，prognostic assessment and efficacy monitoring of HNSCC. However，existing single -omics studies are still limited by low sensitivity and tumor heterogeneity. Multi -omics integration strategies combining genomic，transcriptomic，epigenomic，and proteomic information can significantly enhance diagnostic accuracy and reveal disease molecular mechanisms. In recent years，as deep learning and machine learning technologies have been widely applied to analyze multi-omics data of cfDNA，promoting relevant marker screening and model construction. Existing research indicates that multiomics models based on cfDNA hold promise for improving early diagnosis of HNSCC and offer new directions for precision medicine development.