NEW DELHI New Delhi: Artificial intelligence (AI) can accurately detect early-stage metabolic-associated steatotic liver disease (MASLD) using electronic health records, a study found on Saturday. MASLD – the world's most common chronic liver disease Liver disease, which has a high clinical burden, occurs when fat in the liver is not properly managed. The global prevalence of MASLD has been increasing in recent years.

It is also often associated with other common diseases such as obesity, type-2 diabetes and abnormal cholesterol levels. Since this condition can quickly turn into more serious forms of liver disease, early diagnosis is important. However, it is often not detected until the later stages, as it remains asymptomatic in the early stages, making diagnosis challenging.

“A significant proportion of patients meeting criteria for MASLD remain undiagnosed,” said lead author Ariana Stuart of the University of Washington, US. “This is worrying, because delaying early diagnosis increases the chance of developing advanced liver disease.” The team used an AI algorithm to analyze imaging findings in electronic health records from three sites in the US. While 834 patients met the criteria for MASLD, only 137 had an official MASLD- diagnosis in their records.

This left 83 percent of patients undiagnosed, even though data in their electronic health records showed they met criteria for MASLD. Stuart said the study “shows how AI can overcome the limitations of traditional clinical practice.” The study will be presented at the Liver Meeting, organized by the American Association for the Study of Liver Disease. Previous studies have shown that AI can be used to treat liver fibrosis. Can be done to detect and diagnose non-alcoholic fatty liver disease (NAFLD). It may also help differentiate focal liver lesions, diagnose hepatocellular cancer, predict chronic liver disease (CLD), and facilitate transplantation science.