Marika NiihoriProfessor Mihaela van der Schaar will deliver a State-of-the-Art Lecture at EASL Congress 2026 in Barcelona, taking place from 27–30 May 2026.
EASL Congress (European Association for the Study of the Liver) is Europe’s largest meeting dedicated to liver health, bringing together more than 8,000 clinicians, scientists, allied health professionals, patients, and industry partners from across the field of hepatology.
Her keynote will explore how machine learning is moving beyond static prediction toward dynamic AI systems capable of reasoning about disease progression, treatment response, patient heterogeneity, transplantation pathways, and complex clinical decision-making in hepatology.
As machine learning increasingly intersects with biology and medicine, the talk will examine the transition from predictive models built on genomic and multi-omics data toward AI agents and digital twins that can simulate trajectories, reason about interventions, and adapt as new patient data becomes available.
“In hepatology, this matters deeply,” said Professor van der Schaar. “Liver disease is dynamic, heterogeneous, and shaped by biology, behaviour, comorbidities, interventions, and time.”
The keynote will revisit foundational work in self-supervised learning for genomic risk estimation and multi-view learning for multi-omics integration, before exploring more recent advances in AI agents and digital twins designed to model individual disease trajectories and personalised responses to therapeutic interventions.
A central theme of the talk will be the need to develop a new generation of digital twins grounded not only in clinical biomarkers, but also in the molecular complexity of each individual. By integrating longitudinal clinical data with genomic and multi-omics signals, these systems may enable more personalised simulations of disease progression and treatment response.
The talk will also address what cutting-edge machine learning can realistically achieve for hepatology today, where the most promising frontiers are emerging, and what remains necessary to make these systems trustworthy, clinically meaningful, and useful in practice.
“Most of all, I am excited to discuss these ideas with hepatologists and learn from their clinical perspective, so that the ML we develop is shaped by the real problems, constraints, and opportunities in liver health,” she said.
Professor van der Schaar said she is looking forward to contributing to the wider conversation at EASL Congress 2026 on the future of AI in hepatology and how next-generation machine learning systems can support more personalised, actionable, and biologically informed patient care.
If you are attending the EASL Congress, Prof van der Schaar’s talk is scheduled on Wednesday, 27 May, 17:00 – 17:45 CEST.
