Digital Technologies and Clinical Data Analytics in Hepatopancreatobiliary Diseases: Diagnosis, Treatment, and Beyond

Building on the success of our previous Research Topic Digital Technologies in Hepatology: Diagnosis, Treatment, and Epidemiological Insights. and given the continued importance and growing interest in this subject area, we have decided to expand upon this theme and launch a new Research Topic.

With the rapid advancement of information technology, the field of hepatopancreatobiliary (HPB) medicine has witnessed significant innovations through the application of digital medical technologies. These advancements include the use of artificial intelligence (AI), big data analysis, and their applications in epidemiological studies, enhancing the accuracy of diagnostics and treatment modalities. Despite these advances, challenges remain in early diagnosis and developing truly personalized treatment strategies. Current research is focused on digital medical technologies, such as advanced data collection and processing technologies, and how these can optimize existing medical processes and promote the development of personalized medicine.

The goal of this Research Topic is to explore how digital technologies and clinical data analytics can be more effectively applied in the prevention, diagnosis, treatment, and management of HPB diseases. Specifically, the topic will examine the role of AI-driven imaging tools, multi-dimensional data pipelines, and real-world evidence in shaping precision hepatology. By integrating computational models with clinical expertise, the goal is to promote a data-centric ecosystem that drives innovation, improves patient outcomes, and advances global HPB disease management.

To delve deeper into this field, we have expanded the research scope and themes to explore and advance the application of medical technologies in HPB disease management. This includes:
o Explainable AI and model validation in HPB imaging, surgical planning, and prognostic scoring — with emphasis on prospective validation and clinical calibration
o Data standardization, interoperability, and federated learning enabling reliable multicenter HPB research across heterogeneous EHR systems
o Digital HPB disease diagnostics and therapeutics, including AI-assisted imaging, telemedicine, and automated image interpretation.
o Epidemiology of HPB diseases through global data integration and pattern recognition.
o Clinical data mining and real-world evidence from electronic health records, registries, and cohorts to evaluate treatment outcomes.
o Digital innovations in biliary, pancreatic, and splenic disease management, including radiomics and neuro-hormonal analytics.
o Ethical, regulatory, and economic frameworks for implementing digital health solutions in clinical HPB

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Artificial Intelligence (AI) in Hepatopancreatobiliary Medicine, Digital Health Technologies, Big Data Analytics and Clinical Data Mining, Precision Medicine and Personalized Therapeutics, Hepatopancreatobiliary (HPB) Disease Epidemiology

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.