Digital twins, succinctly described as the digital representation of a physical object, is a concept that has emerged relatively recently with increasing application in the manufacturing industry. This article proposes the application of this concept to the healthcare domain to provide enhanced clinical decision support and enable more patient‐centric, and simultaneously more precise and individualized care to ensue. Digital twins combined with advances in Artificial Intelligence (AI) have the potential to facilitate the integration and processing of vast amounts of heterogeneous data stemming from diversified sources. Hence, in healthcare this can provide enhanced diagnosis and treatment decision support. In applying digital twins in combination with AI to complex healthcare contexts to assist clinical decision making, it is also likely that a key current challenge in healthcare; namely, providing better quality care which is of high value and can lead to better clinical outcomes and a higher level of patient satisfaction, can ensue. In this focus article, we address this proposition by focusing on the case study of cancer care and present our conceptualization of a digital twin model combined with AI to address key, current limitations in endometrial cancer treatment. We highlight the role of AI techniques in developing digital twins for cancer care and simultaneously identify key barriers and facilitators of this process from both a healthcare and technology perspective. This article is categorized under:Application Areas > Health Care In applying digital twins to healthcare we extrapolate from the typical approach used manufacturing and illustrate with a simple example of a car battery. Here multi‐spectral data is collected that will assist to determine the life of the battery so that the mechanic decision maker can decide when is prudent and opita to replace the battery. Translating this to the healthcare domain with an oncology patient we similarly collect multi‐spectral healthcare data that is relevant and pertinent for the clinician decision maker to assess the best treatment protocol and survivorship of the presenting patient. Clearly, the healthcare system is more complex than that of a car battery especially as healthcare deals with biological systems that are messy and complex; however the underlying principles are similar. [ABSTRACT FROM AUTHOR]