Development of a classification model for non ‐alcoholic steatohepatitis (NASH) using confocal Raman micro‐spectroscopy

Abstract Non‐alcoholic fatty liver disease (NAFLD) is the most common liver disorder in developed countries [1]. A subset of individuals with NAFLD progress to non‐alcoholic steatohepatitis (NASH), an advanced form of NAFLD which predisposes individuals to cirrhosis, liver failure and hepatocellular carcinoma. The current gold standard for NASH diagnosis and staging is based on histological evaluation, which is largely semi‐quantitative and subjective. To address the need for an automated and objective approach to NASH detection, we combined Raman micro‐spectroscopy and machine learning techniques to develop a classification model based on a well‐established NASH mouse model, using spectrum pre‐processing, biochemical component analysis (BCA) and logistic regression. By employi...

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