"AI Revolutionizes Early Diagnosis of Liver Disease: Breakthrough Study Insights"

"AI Revolutionizes Early Diagnosis of Liver Disease: Breakthrough Study Insights"

 According to a study published on Saturday, artificial intelligence (AI) can reliably identify metabolic-associated steatotic liver disease (MASLD) in its early stages using electronic medical information. When fat in the liver is not adequately maintained, it can lead to MASLD, the most prevalent chronic liver disease in the world with a significant clinical burden. In recent years, MASLD has become more commonplace worldwide.

It is frequently linked to other prevalent illnesses like Type 2 diabetes, obesity, and elevated cholesterol. Early detection is essential since the disorder can rapidly worsen into more severe forms of liver disease. However, because it is difficult to diagnose in its early stages and remains asymptomatic, it frequently goes unnoticed until later.

According to lead author Ariana Stuart of the University of Washington in the United States, "a considerable proportion of patients who fulfill the criteria for MASLD go misdiagnosed." "Delays in early diagnosis raise the risk of development to advanced liver disease, which is alarming."

The team analyzed imaging results in electronic health records from three US locations using an AI system. Only 137 of the 834 individuals who satisfied the criteria for MASLD had a formal diagnosis linked to MASLD in their medical records. Despite information in their electronic health records indicating they fit the criteria for MASLD, 83% of patients remained undiagnosed.

"This study demonstrates how AI may enhance physician processes to overcome the constraints of conventional clinical practice," . The American Association for the findings of Liver Diseases is hosting The Liver Meeting, where the findings will be presented. AI can be used to diagnose non-alcoholic fatty liver disease (NAFLD) and identify liver fibrosis, according to earlier research. Additionally, it can aid in the diagnosis of hepatocellular cancer, the prognosis of chronic liver disease (CLD), the differentiation of focal liver lesions, and the advancement of transplant technologies.