Helen Ye Rim Huang, Kai Markus Schneider, Carolin Schneider
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Big Data Analytics in Large Cohorts: Opportunities and Challenges for Research in Hepatology.
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.
期刊介绍:
Seminars in Liver Disease is a quarterly review journal that publishes issues related to the specialties of hepatology and gastroenterology.
As the premiere review journal in the field, Seminars in Liver Disease provides in-depth coverage with articles and issues focusing on topics such as cirrhosis, transplantation, vascular and coagulation disorders, cytokines, hepatitis B & C, Nonalcoholic Steatosis Syndromes (NASH), pediatric liver diseases, hepatic stem cells, porphyrias as well as a myriad of other diseases related to the liver. Attention is also given to the latest developments in drug therapy along with treatment and current management techniques. Seminars in Liver Disease publishes commissioned reviews. Unsolicited reviews of an exceptional nature or original articles presenting remarkable results will be considered, but case reports will not be published.