Fig. 1: Deep Learning-based classification of HCC versus ICCA.
From: Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma
A Clinical problem: combined HCC-CCA tumors are a diagnostic dilemma and only poor evidence is available to guide treatment in these patients. We hypothesize that an AI system can reclassify all cHCC-CCA cases into either category. B Technical approach: a two-step pipeline is used to transform image tiles into feature vectors by model 1 (M1), a pre-trained feature extraction model. A bag of feature vectors is subsequently aggregated into a call for a given patient by model 2 (M2), the aggregation model. C Experimental approach: a binary prediction model was trained to distinguish HCC from CCA and was evaluated via cross-validation and by external validation. Subsequently, the trained model was applied to a multicentric cohort of cHCC-CCA tumors and its predictions were comprehensively validated with a multimodal approach.
