The field of surgery is undergoing a historic paradigm shift from experience-based medicine towards precision and intelligence. However, the integration gap between medical science, engineering, and mathematical technologies severely constrains the depth and breadth of surgical intelligence. This article conducts an in-depth analysis of the critical barriers currently hindering medical-engineering-mathematical (MEM) integration within surgery. It systematically elucidates the pivotal driving role of artificial intelligence (AI) technologies-particularly deep learning, computer vision, natural language processing, and multimodal fusion-in bridging these gaps. By integrating international case studies and institutional practices in hepatobiliary and pancreatic surgery, including AI-assisted planning, real-time intraoperative navigation, and intelligent postoperative management, this work demonstrates how AI effectively bridges the MEM intelligent integration gap. Furthermore, it proposes the construction of an integrated MEM innovation ecosystem framed around “talent cultivation，a foundational data infrastructure，collaborative platforms，and ethical safeguards”. The article concludes by envisioning the future landscape of an AI-empowered, intelligent surgical ecosystem. AI is emerging as the core engine propelling surgery across the MEM integration gap, thereby accelerating the field′s entry into a new era of intelligence.

The field of surgery is undergoing a historic paradigm shift from experience-based medicine towards precision and intelligence. However, the integration gap between medical science, engineering, and mathematical technologies severely constrains the depth and breadth of surgical intelligence. This article conducts an in-depth analysis of the critical barriers currently hindering medical-engineering-mathematical (MEM) integration within surgery. It systematically elucidates the pivotal driving role of artificial intelligence (AI) technologies-particularly deep learning, computer vision, natural language processing, and multimodal fusion-in bridging these gaps. By integrating international case studies and institutional practices in hepatobiliary and pancreatic surgery, including AI-assisted planning, real-time intraoperative navigation, and intelligent postoperative management, this work demonstrates how AI effectively bridges the MEM intelligent integration gap. Furthermore, it proposes the construction of an integrated MEM innovation ecosystem framed around “talent cultivation，a foundational data infrastructure，collaborative platforms，and ethical safeguards”. The article concludes by envisioning the future landscape of an AI-empowered, intelligent surgical ecosystem. AI is emerging as the core engine propelling surgery across the MEM integration gap, thereby accelerating the field′s entry into a new era of intelligence.

Laparoscopic or robotic minimally invasive liver resection is the core treatment for liver cancer, but the safety and thoroughness of the surgery still face many challenges. In recent years, with the in-depth development of medical-industrial interdisciplinary, digital intelligent dia-gnosis and treatment technologies, which are deeply formed by the integration of digital medical technology, big data and artificial intelligence, have injected new vitality into the minimally invasive surgical treatment of liver cancer, brought a brand-new perspective, and promoted the transforma-tion of the traditional surgical paradigms into the modern minimally invasive, precise and intelligent surgical models. The authors summarize the development of digital intelligent minimally invasive surgical treatment of liver cancer over the past 20 years, discuss the evolution from clinical problems to key scientific issues, and from clinical needs to technological innovations. By reviewing past progress and looking forward to future directions, it aims to further promote the innovation of digital intelligent minimally invasive surgical techniques to improve the prognosis of patients with liver cancer.

Due to the inherently complex anatomical structure and physiological charac-teristics of the biliary system, biliary surgery faces considerable challenges in key stages such as preoperative planning, intraoperative identification, and postoperative management. These challenges contribute to a persistently high incidence of complications, severely affecting patient prognosis and overall survival. In recent years, with the continued advancement of interdisciplinary integration between medicine and engineering, intelligent digital technologies, centered on digital medicine, big data, and medical artificial intelligence, have been increasingly applied in the field of biliary surgery, offering new solutions to these longstanding problems. The authors systematically review recent advances and clinical applications of intelligent digital technologies in biliary surgery, and explore the evolution from clinical needs to technological innovation and practical implementation. The aim is to facilitate the transition of biliary surgery from an experience-based approach to an intelligent and precision-driven paradigm, thereby improving surgical safety and patient outcomes.

Laparoscopic or robotic minimally invasive liver resection is the core treatment for liver cancer, but the safety and thoroughness of the surgery still face many challenges. In recent years, with the in-depth development of medical-industrial interdisciplinary, digital intelligent dia-gnosis and treatment technologies, which are deeply formed by the integration of digital medical technology, big data and artificial intelligence, have injected new vitality into the minimally invasive surgical treatment of liver cancer, brought a brand-new perspective, and promoted the transforma-tion of the traditional surgical paradigms into the modern minimally invasive, precise and intelligent surgical models. The authors summarize the development of digital intelligent minimally invasive surgical treatment of liver cancer over the past 20 years, discuss the evolution from clinical problems to key scientific issues, and from clinical needs to technological innovations. By reviewing past progress and looking forward to future directions, it aims to further promote the innovation of digital intelligent minimally invasive surgical techniques to improve the prognosis of patients with liver cancer.

Due to the inherently complex anatomical structure and physiological charac-teristics of the biliary system, biliary surgery faces considerable challenges in key stages such as preoperative planning, intraoperative identification, and postoperative management. These challenges contribute to a persistently high incidence of complications, severely affecting patient prognosis and overall survival. In recent years, with the continued advancement of interdisciplinary integration between medicine and engineering, intelligent digital technologies, centered on digital medicine, big data, and medical artificial intelligence, have been increasingly applied in the field of biliary surgery, offering new solutions to these longstanding problems. The authors systematically review recent advances and clinical applications of intelligent digital technologies in biliary surgery, and explore the evolution from clinical needs to technological innovation and practical implementation. The aim is to facilitate the transition of biliary surgery from an experience-based approach to an intelligent and precision-driven paradigm, thereby improving surgical safety and patient outcomes.

Pancreatic surgery remains one of the most challenging fields in general surgery due to its complex anatomy and high risk of complications.In recent years,the integration of digital intelligent technologies-such as three-dimensional(3D)reconstruction,fluorescence navigation,augmented/mixed reality(AR/MR),and artificial intelligence(AI)-has provided new strategies for achieving precision,safety,and intelligence in pancreatic surgery.This review summarizes the innovations and clinical applications of these technologies throughout the full perioperative process,including preoperative planning,intraoperative navigation,and postoperative monitoring.Preoperatively,the deep learning-based nnU-Net framework enables high-precision 3D reconstruction of peripancreatic vessels and pancreaticobiliary ducts for individualized surgical planning.Intraoperatively,multimodal image fusion combining indocyanine green fluorescence imaging with AR/MR navigation allows real-time visualization and spatial localization of key anatomical structures,enhancing surgical accuracy and safety.Postoperatively,AI-driven models integrated with wearable sensors and multimodal data support intelligent risk prediction and early intervention for complications.The systematic application of digital intelligence is reshaping the paradigm of pancreatic surgery,driving the transition from experience-based to data-driven and from surgeon-dependent to intelligent decision-making.With continuous algorithmic refinement and accumulation of clinical evidence,digital empowerment will further advance pancreatic surgery toward personalization,precision,and intelligence.

Pancreatic surgery remains one of the most challenging fields in general surgery due to its complex anatomy and high risk of complications.In recent years,the integration of digital intelligent technologies-such as three-dimensional(3D)reconstruction,fluorescence navigation,augmented/mixed reality(AR/MR),and artificial intelligence(AI)-has provided new strategies for achieving precision,safety,and intelligence in pancreatic surgery.This review summarizes the innovations and clinical applications of these technologies throughout the full perioperative process,including preoperative planning,intraoperative navigation,and postoperative monitoring.Preoperatively,the deep learning-based nnU-Net framework enables high-precision 3D reconstruction of peripancreatic vessels and pancreaticobiliary ducts for individualized surgical planning.Intraoperatively,multimodal image fusion combining indocyanine green fluorescence imaging with AR/MR navigation allows real-time visualization and spatial localization of key anatomical structures,enhancing surgical accuracy and safety.Postoperatively,AI-driven models integrated with wearable sensors and multimodal data support intelligent risk prediction and early intervention for complications.The systematic application of digital intelligence is reshaping the paradigm of pancreatic surgery,driving the transition from experience-based to data-driven and from surgeon-dependent to intelligent decision-making.With continuous algorithmic refinement and accumulation of clinical evidence,digital empowerment will further advance pancreatic surgery toward personalization,precision,and intelligence.

As 2021 is known as the “first year of the metaverse”, the concept of metaverse is promoting a multi-field innovation revolution on a global scale. The new experiences and technologies it brings are expected to provide solutions for the difficulties in the field of human visualization surgery in disease diagnosis, preoperative planning, surgical treatment, medical education, health management and patient experience. This opens up opportunities for the next wave of disruptive technology innovation. This paper proposes a new concept of “human visualization metaverse”, and summarizes its innovative application, future development direction and challenges to promote the research and development of human visualization metaverse,and to explore the application potential of metaverse technology in the field of surgery to advance the research and development of the metaverse for human visualization.

The emergence and evolution of digital intelligent technology has profoundly influenced the development of minimally invasive research-oriented hepatobiliary and pancreatic surgery discipline. Over various periods, our team has always adhered to the principle of "being oriented by clinical issues and driven by clinical needs", continuously carried out innovative research across interdisciplinary boundaries, propelling the evolution of digital intelligent technology. Spanning over two decades, this journey includes the progression from digital virtual human, three-dimensional visualization, molecular fluorescence imaging, augmented reality and mixed reality, artificial intelligence, to the realm of human visualization meta-universe. This evolution facilitates the shift from two-dimensional empirical diagnoses of hepatobiliary and pancreatic surgical diseases to deep learning intelligent diagnostics, the transition from morphology-based tumor diagnoses to molecular imaging-based diagnostics, and from conventional empirical surgery to intelligent navigation surgery. The authors provide a comprehensive review of our developmental process and achievements within the realm of digital intelligent diagnostic and therapeutic technologies, with the aims to promote the development and application of digital intelligent medicine.