Fatty liver disease affects about 30 percent of adults worldwide and often remains undetected until severe liver damage becomes life-threatening. Researchers believe artificial intelligence could help identify high-risk patients earlier by analysing large volumes of routine health records and laboratory results, potentially allowing treatment before the disease progresses.

Early-stage liver damage can often be reversed through changes such as weight loss, improved diet, exercise and reduced alcohol intake, while medicines including semaglutide and resmetirom may help more advanced cases. Existing tests, including the Fib-4 index and enhanced liver fibrosis test, can improve detection of serious scarring, but are not routinely used; AI could make risk assessment easier without adding substantially to clinicians’ workload.