Advancing liver cancer diagnosis and treatment with multi-omics approaches: a systematic review

From a clinical perspective, multi-omics integration coupled with machine learning holds immense potential for improving early diagnosis, patient stratification, and therapeutic targeting. However, challenges related to data integration, interpretability, and cohort diversity must be addressed to realize this potential. This review underscores the transformative role of machine learning-enhanced multi-omics in reshaping liver cancer diagnosis and treatment and outlines future directions to bridge the gap between computational advances and clinical application.