Predicting Early Recurrence Risk in Tanzanian Breast Cancer Patients

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Our study focuses on predicting Biochemical Recurrence (BCR) in Tanzania by exploring its global burden and specific local recurrence rates. We aim to pinpoint key clinical and molecular risk factors using machine learning (ML) to enhance prediction accuracy. Our methodological approach encompasses setting clear objectives, collecting robust data, and selecting suitable ML models for precise outcome prediction. The results reveal critical predictors, evaluate model effectiveness, and...