New digital twin framework simulates liver health progression

Researchers have developed HEPATWIN, a novel digital twin framework for simulating liver health progression. This physiology-informed model integrates metabolic processes and patient-specific inputs to predict biomarker trajectories over time. Validation against the NIDDK NAFLD dataset shows HEPATWIN can forecast multi-year health outcomes and support downstream disease detection. AI

IMPACT This framework could advance personalized diagnostics and prediction of organ health, particularly for liver conditions.

RANK_REASON The cluster contains a research paper detailing a new computational framework for simulating biological processes. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• fibrosis
• HEPATWIN
• liver cirrhosis
• metabolic dysfunction–associated steatotic liver disease
• Nash
• NIDDK NAFLD dataset
• Sumaiya Afroz Mila

• paper
• model release

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