Cancer Screening

Cancer screening, particularly for breast cancer, aims to detect malignancies early for improved treatment outcomes. Current research heavily emphasizes the development and refinement of AI-driven diagnostic tools, utilizing diverse approaches such as convolutional neural networks, transformers, and novel algorithms like self-contrastive learning, often incorporating multi-modal imaging data (mammography, ultrasound, thermography) and electronic health records. These advancements aim to increase diagnostic accuracy, reduce the burden on healthcare systems, and improve risk stratification for personalized screening strategies, ultimately leading to earlier detection and better patient care.