Cancer is a leading cause of morbidity and mortality worldwide. Accurate diagnosis of disease type and molecular profile are crucial for effective and targeted therapy to patients. Additionally, cancer is a dynamic process, both clinically and at the molecular level and therefore useful tools for disease monitoring could help tailor personalized treatment for each patient. Our research focuses of developing better diagnostic tools, both at the molecular level and the histomorphological level. Toward this aim we establish tissue specific, next generation sequencing (NGS) mutational panels – to identify the common cancer drivers in each tumor type. Additionally, we apply deep learning and artificial intelligence for the development of algorithms that improve microscopy based diagnosis. These algorithms come on top of our digital pathology platform, used for routine diagnosis. Another significant focus of our research is aimed at monitoring cancer progression and response to therapy. This is done via analysis of circulating tumor DNA.