Abstract

Liver fibrosis, a progressive condition resulting from chronic liver injury, poses significant challenges for early detection and effective management. The review paper explores the current and emerging biomarkers for liver fibrosis, emphasizing the integration of multi-marker approaches and technological advancements in clinical practice. It discusses traditional serological, imaging, and histological biomarkers and delves into emerging genomic, proteomic, non-coding RNA, and metabolomic biomarkers. The paper highlights the potential of artificial intelligence and machine learning in biomarker discovery and interpretation and addresses regulatory, logistical, and cost issues. The future of liver fibrosis management is envisioned through innovations that promise early detection, personalized treatment, and non-invasive monitoring, ultimately improving patient outcomes and quality of life.