Abstract
Trans-arterial chemoembolization (TACE) is a loco-regional therapy with survival benefit for patients with hepatocellular carcinoma. LI-RADS 2018 treatment response algorithm assesses tumor viability. Large image datasets that are segmented and prepared for analysis are difficult to obtain. Our purpose was to train a machine learning classifier to predict LI-RADS treatment response status based on the pre-treatment MRI and evaluate efficacy of data processing techniques for a small dataset.
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