New Delhi, November 16 (IANS). A study has revealed that Artificial Intelligence (AI) can accurately detect early-stage Metabolic-Associated Statistic Liver Disease (MASLD) using electronic health records.
Metabolic-associated steatotic liver disease (MASLD) is the most common chronic liver disease in the world. This disease occurs due to improper accumulation of fat in the liver, which leads to serious health problems. Cases of this disease are increasing rapidly in the last few years.
It is also often associated with other common diseases such as obesity, type 2 diabetes and abnormal cholesterol levels.
This condition can rapidly develop into more serious forms of liver disease, so early detection is important. However, it is often not detected until the late stages because the disease has no symptoms in the early stages, making it challenging to detect.
“A large number of patients with metabolic-associated steatotic liver disease (MASLD) are not diagnosed in time,” said lead author Ariana Stuart of the University of Washington in the US. This is very worrying because delay in early diagnosis increases the risk of liver disease.
The team used AI algorithms to analyze imaging findings in electronic health records from three sites in the US. Symptoms of fatty liver disease were found in 834 patients, but the records included data of only 137 patients.
Of these, the disease could not be detected in 83 percent of the people, while all of them had symptoms of the disease. The research 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 detect liver fibrosis 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.
–IANS
MKS/AS
