Causal multi-modal AI for personalized chemosensitivity prediction

A causal multi-modal AI model was developed to predict personalized chemosensitivity in breast cancer patients using routine pathology and clinical data. Trained on 9,141 patients from nine countries and validated on 1,994 patients from three countries, the model produced treatment-specific recurrence probabilities with near-perfect calibration and strong prognostic discrimination over 5- and 10-year horizons. It outperformed existing recurrence-score tests and could reduce chemotherapy prescriptions by 30% while maintaining recurrence-free rates, with predictive performance also transferring to non-breast cancers.

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• multimodal