Poster

Validation of a Machine Learning-Based Approach (DELTA Liver Fibrosis Score) for the Assessment of Histologic Response in Patients with Advanced Fibrosis due to NASH

AASLD 2020

Study Background

♦Fibrosis, as assessed by liver biopsy, is the primary determinant of disease progression in patients with nonalcoholic steatohepatitis (NASH)

♦ Liver biopsy plays an integral role in the diagnosis and monitoring of disease progression, both in routine clinical practice and clinical trials

♦ Human pathologist staging of fibrosis is limited by intra- and inter-reader variability

♦ Machine learning (ML) approaches to interpretation of liver histology may enable more reliable and quantitative assessment of both traditional and novel histologic features, with potential prognostic relevance in NASH
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Authors

Taylor-Weiner et al