Advancing precision pathology: data-driven AI for medical image analysis

Cancer has emerged as a leading cause of death globally, presenting a significant and increasing threat to public health systems. Nowadays, computational pathology has become a promising interdisciplinary approach. This thesis presents four innovative deep learning-based computational pathology neural networks. Each network specifically addresses a specific challenge in this research community. The outcomes from these advancements hold great promise for significantly improving patient outcomes, optimizing resource utilization, and ultimately advancing the overall efficacy and sustainability of healthcare systems worldwide.