
Machine Learning-Driven Noninvasive Prediction of Liver Fibrosis in Unclassified Liver Disease
Chronic liver diseases (CLDs) frequently progress silently to advanced fibrosis or cirrhosis, yet existing predictive models have largely been developed for patients with clearly defined etiologies. Here, we asked whether a noninvasive machine-learning model based on routine clinical variables and liver stiffness measurement (LSM) could accurately identify significant liver fibrosis in patients with CLD of uncertain etiology, and whether such a model would add value beyond conventional fibrosis scores for clinic…
MedComm
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