The Digital Twin: Modular Model-Based Approach to Personalized Medicine

Abstract

To overcome obstacles and complexity of decision making in clinical oncology, we propose an integrated clinical decision support approach; the Digital Twin. We analyse the reasons for frustration in applying clinical decision support and provide a multi-levelled approach to implementing a flexible system to support and strengthen clinical decisions. Describing medical patterns and contexts with Resource Description Framework (RDF) allows for standardised way of connecting medical knowledge and processing modules. Having flexible web-based interfaces integrated a multitude of heterogeneous data processing systems to either make clinical data available altogether, or provide calculations and assessments. Transition of the Digital Twin to clinical practice promises effective assistance and safer clinical decisions.