Cervical Cancer

Cervical cancer research focuses on improving early detection and treatment, primarily through automated image analysis of Pap smears, colposcopies, and MRI scans. Current efforts leverage deep learning, employing convolutional neural networks (CNNs), transformers, and hybrid architectures like those incorporating attention mechanisms and residual connections, to classify cancerous cells, segment tumors, and predict radiation dose distributions. These advancements aim to increase diagnostic accuracy, reduce human error, and improve treatment planning, ultimately leading to better patient outcomes and more efficient healthcare resource allocation.