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This paper presents an Attention-Based Multiple Instance Learning (ABMIL) framework that leverages patient-level labels from cancer registries to train deep learning classifiers for tumor group classification without requiring per-report annotations, achieving a macro F1 of 0.83 on tasks at the BC Cancer Registry.