Convergence of digital technologies for cancer

The accelerated pace of advances in digitalization, connectivity, and computing will continue to disrupt oncology. This convergence of technology and medicine has paved the way for innovations that promise to dramatically increase the precision and personalization of care, transforming cancer care from a one-size-fits-all approach to one that is truly patient centric and patient participatory. By integrating multimodal data sources - from genomic sequences to digital images and wearables - oncologists will have the ability to design optimal longitudinal treatments that are related to the desired clinical outcomes of the patient. This next level of personalization will motivate the engineering and mining of vast datasets for hidden patterns that can predict disease trajectory and response to treatment, and even unveil new therapeutic targets. It will also drive the development of novel measurement technologies (e.g., diagnostics, imaging, sentiment, outcomes) that are made increasingly sensitive and specific through advances in computing and machine learning techniques. This chapter aims to provide an overview of these technologies and their application in oncology, presenting both their potential and the challenges they bring.