We are living in an age of intensive transformation. Ranging from industrial systems up to patient care in both acute or chronic conditions is transforming, moving from simplistic view, with arbitrary interval checks hoping to observe common ground of functional and structural changes under the stress of the environment, to complex view where holistic systems are now paired with their digital twins. The current effort aims to provide an extended view of both humans or technical systems, able to capture the state of facts and provide assistance when, where and how is needed.
iHelp plans to leverage the concept of Digital Twin and use it to provide to all actors involved in patient monitoring and care a comprehensive view with a multidisciplinary impact of past, present and potential future clinical interventions. Pancreatic Cancer represents a complex type of clinical situation where each affected person exposes a multitude of preconditions. AI-augmented Digital Twin of a patient is expected to pave the pathway to a fitted personalized care where individual aspects are considered.
Siemens, as part of the project, is looking from two different angles. One is related to previous domain experience, related not only to healthcare portfolio but also to predictive intelligence associated with industry grade infrastructures, the so-called Operational Technology (OT). The second view talks about the largely available services and products which are capable to encode, abstract, model and analyze operational data in the Information Technology (IT) space. The aim is the efficient and secure fusion between those two worlds where operational space is extended in the IT-sphere using cloud-based services, scaling and integrating IoT -Edge – Cloud data spaces in a single continuum. Associated analytics and AI techniques can then be applied to data segments either at the level of individuals, cohorts or special types of the population under consideration.
The way towards impact generation in personalized care comprises of many individual steps. As for the current phase of the project, Siemens is setting up together with project partners analytics workflows capable to grow together data acquisition towards on the so-called Knowledge Graph – as an aggregated instrument capable to bundle data, historian and processes associated with one identity, a holistic view of Digital Twin associated with a clinical case.
