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AI-based MASH CRN scoring: CNN pixel-level predictions for each histological feature (for example, fibrosis or steatosis) were clustered using GNN models and a score predicted based on the spatial organization of the cluster. To correct for pathologists bias, the GNN models were specified as mixed effects models, biases were learned and the GNNs were deployed with predictions using only the unbiased estimate. GNN nodes and edges were built from CNN predictions of relevant histologic features derived from deployment of the H&E, MT and artifact models.

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