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A novel temporal graph framework achieves over 250x fewer FLOPs and 20x fewer parameters than Transformers/LSTMs for early gastrointestinal cancer risk stratification from sparse EHRs.
A Transformer trained on routine blood tests and clinical histories can predict pancreatic cancer years before diagnosis, opening the door to effective population-level screening.