Breast Cancer Recurrence Prediction: A High-Performance Deep Learning Approach on Clinical Data
This study presents a high-performance deep learning model using the METABRIC dataset that achieves a new benchmark in breast cancer recurrence prediction by attaining 100% precision, thereby demonstrating that sophisticated data engineering and network architecture can outperform complex multi-modal approaches even with limited clinical data.