AI Technology Pinpoints Liver Disease Earlier Than Ever
A recent study suggests that artificial intelligence (AI) can play a crucial role in the early detection of fatty liver disease. Researchers used an AI system to analyze electronic health records within the University of Washington Medical System and identify cases of metabolic-associated steatotic liver disease (MASLD), a common form of fatty liver disease. The AI was able to uncover hundreds of undiagnosed cases that were missed by traditional clinical methods.
Dr. Ariana Stuart, the lead researcher and a resident at the University of Washington, highlighted that a significant number of individuals who meet the criteria for MASLD go undiagnosed. She pointed out that delayed diagnosis can increase the risk of the disease progressing to more advanced liver conditions. The AI system identified 834 patients with fatty liver disease based on imaging scans, yet only 137 had a formal diagnosis in their medical records, meaning that 83% of those affected were not diagnosed despite evidence in their health records.
Dr. Stuart presented the findings at the American Association for the Study of Liver Diseases annual meeting in San Diego. While the results are promising, she cautioned that the study is still preliminary and should not be interpreted as a critique of primary care practices. Rather, the research demonstrates how AI can support doctors by addressing the limitations of traditional clinical workflows.
Fatty liver disease is increasingly common, affecting up to 42% of U.S. adults, with obesity, excessive alcohol consumption, and type 2 diabetes being major contributing factors. If left untreated, the condition can lead to liver scarring and increase the risk of liver disease and cancer. Early detection is essential to prevent these complications and manage the disease before it worsens, making AI a potentially valuable tool in healthcare.
Discussion about this post