From diagnosis to recovery — AI leads the future of liver treatment.
Artificial intelligence (AI) is rapidly reshaping the landscape of healthcare from diagnostics and treatment planning to surgical assistance and administrative efficiency. In liver care, AI holds enormous promise, particularly in managing complex conditions like cirrhosis, liver cancer, and transplantation logistics. However, as with any powerful tool, it must be handled with precision, ethics, and cultural sensitivity.
At the recent European Association for the Study of the Liver (EASL) Congress 2025 in Amsterdam, Dr. Ashley Spann, a transplant hepatologist from Vanderbilt University Medical Center, delivered a critical message: AI in hepatology must be designed and implemented with vigilance, tailored to the population it serves, and monitored continuously to prevent harm.
AI in Liver Care: A Double-Edged Sword
Dr. Spann, known for her work in informatics and AI-driven liver care, emphasized a core concern—while AI can streamline decision-making and predict patient outcomes more effectively than traditional methods, it’s only as reliable as the data and assumptions it’s built on.
“We need to include patients and providers from the very beginning, not build in silos,” she stated. “The data must be representative of the population of concern, the technical solution must fit the clinical problem, and the model must not cause harm.”
This highlights a recurring theme in AI ethics: bias in training data can lead to real-world consequences, especially in underrepresented or diverse populations. Liver diseases, for example, can manifest differently across ethnicities due to genetic, environmental, and socioeconomic factors. If AI models are trained predominantly on data from one group, they may misdiagnose or mismanage others.
Ethics Still Apply in a Digital World
Dr. Spann reminded attendees that traditional medical ethics—particularly the principle of non-maleficence (“do no harm”)—are just as important in the digital age. Many clinicians are eager to embrace AI, often viewing it as a technological breakthrough that will reduce errors and improve efficiency. But without ethical checks and transparent development, AI tools can introduce new risks and widen health disparities.
“AI is already around us,” she said. “The question is: Should we use it? And if so, how do we do it responsibly?”
The answer lies in responsible AI integration, which includes continuous model validation, stakeholder input, and the flexibility to adapt tools based on real-time feedback from clinicians and patients alike.
Best Practices for AI in Hepatology
Dr. Spann outlined several best practices for healthcare organizations and innovators looking to integrate AI in liver clinics:
- Start with Clinical Problems, Not Tech Hype
Develop models around pressing challenges in liver care, such as predicting post-transplant survival, optimizing treatment paths for hepatocellular carcinoma, or managing drug interactions in cirrhosis. - Use Representative Data Sets
Ensure training data reflects the local patient population—across age, gender, ethnicity, and socioeconomic background. Avoid one-size-fits-all models. - Collaborate Cross-Functionally
Involve hepatologists, data scientists, ethicists, and patients in model design and validation. The most effective AI tools are co-created, not top-down. - Implement Regular Monitoring and Feedback Loops
AI isn’t “set it and forget it.” Models must be monitored for performance over time, especially as patient populations or treatment protocols evolve. - Maintain Transparency
Clinicians should understand how AI arrives at its decisions. Black-box algorithms may be powerful, but if they can’t be explained or interpreted, trust will erode.
The Bigger Picture: A Call to Action for Ethical AI
As AI matures in liver care and broader medicine, it’s crucial to balance innovation with responsibility. Cutting-edge tools that disregard ethical and cultural nuance could do more harm than good, even if well-intentioned.
Instead of chasing tech for tech’s sake, the healthcare community must focus on human centered AI—tools that amplify clinician judgment, respect patient individuality, and elevate care outcomes without introducing new risks.
Final Thoughts
The promise of AI in liver care is undeniable but it must be patient-focused, population aware, and ethically governed. As Dr. Spann aptly noted, the question isn’t whether we can use AI in hepatology; it’s how we ensure we’re using it right.
As the medical world races ahead with innovation, let’s remember: better healthcare isn’t just about smarter algorithms, it’s about smarter application.
