Levelup

Breast cancer remains a major global health challenge, where early detection is crucial to reducing mortality rates. This project proposes an advanced machine learning framework that integrates multi-modal data-including clinical records, genomic profiles, and imaging data-to develop a comprehensive breast cancer prediction model. The project leverages publicly available datasets (TCGA, SEER, CBIS-DDSM) and collaborations with medical institutions to create an AI-driven screening tool tailored for both urban and rural populations in China. Our hybrid methodology employs convolutional neural networks (CNNs) for image analysis and transformer-based models for genomic data processing, fused via attention-based integration. Key innovations include dynamic risk stratification, an AI-powered web platform for accessible screening, and interdisciplinary collaboration between AI and healthcare domains. Anticipated outcomes include an accurate, scalable predictive tool for healthcare providers, enhancing early detection and improving survival rates.