Topic: Artificial Intelligence in Hepatobiliary Clinical Practice

Artificial intelligence (AI) is rapidly reshaping the landscape of hepatobiliary clinical practice, offering new opportunities to improve diagnosis, treatment planning, procedural guidance, and outcome prediction. In a field characterized by technical complexity, high-risk decision making, and the integration of multimodal data, AI has the potential to support clinicians across the entire patient pathway, from preoperative assessment to postoperative management and long-term follow-up.

Recent advances in machine learning, deep learning, computer vision, and data-driven predictive modeling have already demonstrated promising applications in hepatobiliary surgery, liver oncology, transplant medicine, and advanced imaging analysis. These technologies may enhance the interpretation of radiological and pathological data, optimize patient selection, support surgical planning, and contribute to more personalized and precise care. At the same time, the translation of AI into routine clinical practice raises important challenges related to validation, interpretability, ethics, data quality, regulatory oversight, and real-world implementation.

This Special Issue aims to provide an updated overview of the current and emerging roles of AI in hepatobiliary clinical practice. We welcome contributions addressing a broad range of topics, including but not limited to clinical decision support systems, imaging-based AI applications, surgical navigation and planning, outcome prediction, perioperative risk stratification, workflow optimization, and the ethical or organizational implications of AI adoption. Both original research and high-quality reviews are encouraged, particularly those with a strong translational or clinical perspective.

By bringing together contributions from clinicians, surgeons, radiologists, data scientists, and interdisciplinary researchers, this Special Issue seeks to stimulate discussion and foster collaboration in a rapidly evolving field that holds great promise for the future of hepatobiliary care. We hope this collection will offer valuable insights into how AI can be responsibly and effectively integrated into clinical practice, ultimately improving patient outcomes and supporting innovation in hepatobiliary medicine and surgery.