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Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction.

David Nam¹, Julius Chapiro¹, Valerie Paradis^2,3

¹Section of Interventional Radiology, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.

JHEP Reports : Innovation in Hepatology

|March 4, 2022

Summary

Artificial intelligence (AI) can extract vital diagnostic and prognostic information from liver disease images. Further validation is needed for AI tools to support clinical decisions in hepatology.

Failed At:

2026-06-19T13:39:26.508587+00:00

Keywords:

AI, artificial intelligence Artificial intelligence CNN, convolutional neural network DICOM, Digital Imaging and Communications in Medicine HCC, hepatocellular carcinoma ML, machine learning MVI, microvascular invasion NAFLD, non-alcoholic fatty liver disease NASH, non-alcoholic steatohepatitis TACE, transarterial chemoembolisation TRIPOD, Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis WSIs, whole slide images deep learning diagnostic support system imaging machine learning multimodal data integration

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