Huang Helen Ye Rim, Schneider Kai Markus, Schneider Carolin
Department of Internal Medicine III, Gastroenterology, Metabolic Diseases and Intensive Care, University Hospital RWTH Aachen, Aachen, Germany.
Division of Translational Medicine and Human Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Semin Liver Dis. 2025 Sep;45(3):315-327. doi: 10.1055/a-2599-3728. Epub 2025 May 21.
Advances in big data analytics, precision medicine, and artificial intelligence are transforming hepatology, offering new insights into disease mechanisms, risk stratification, and therapeutic interventions. In this review, we explore how the integration of genetic studies, multi-omics data, and large-scale population cohorts has reshaped our understanding of liver disease, using steatotic liver disease as a prototype for data-driven discoveries in hepatology. We highlight the role of artificial intelligence in identifying patient subgroups, optimizing treatment strategies, and uncovering novel therapeutic targets. Furthermore, we discuss the importance of collaborative networks, open data initiatives, and implementation science in translating these findings into clinical practice. Although data-driven precision medicine holds great promise, its impact depends on structured approaches that ensure real-world adoption.
大数据分析、精准医学和人工智能的进展正在改变肝病学，为疾病机制、风险分层和治疗干预提供新的见解。在本综述中，我们以脂肪性肝病作为肝病领域数据驱动发现的范例，探讨基因研究、多组学数据和大规模人群队列的整合如何重塑了我们对肝病的理解。我们强调了人工智能在识别患者亚组、优化治疗策略和发现新治疗靶点方面的作用。此外，我们讨论了合作网络、开放数据倡议和实施科学在将这些发现转化为临床实践中的重要性。尽管数据驱动的精准医学前景广阔，但其影响取决于确保在现实世界中应用的结构化方法。
