Digital Health

Empower data-driven decisions Digital simulations and AI support better decision making 

How can healthcare benefit from technology?

High quality data with advanced analytics and AI companions enable healthcare providers to make smarter decisions:

  • Longitudinal patient and cohort data from imaging, laboratory and genomics can help to improve clinical decisions in single interventions, along patient pathways or across whole populations.
  • Enterprise-wide, real-time, operational data is needed for better operational decisions targeting single asset and fleets, workflows and workforce or the overall enterprise performance.
  • Consumer decision-making benefits from self-scheduling, health informatics or even predictive wellness coaches.
Clinical decision support

Patient data for
clinical decision support

longitudinal data on patients, e.g. EHR, imaging, labs, genomics, behavioral data both from the individual patient, and from the vast pool of comparable cases

Analytics and AI used for:

outcome predictions, diagnostic and therapy decision support or chronic disease management, episodic or longer-term

In the future, a model, or "digital twin", of the patient might be available and treatment alternatives could be explored in the virtual world before setting off on a care pathway in the real world.

Operational decision support

Hospital data for
operational decision support

Data input:
enterprise-wide data, real-time, operational data, e.g. workflows, patient flows, staff scheduling, productivity

Analytics and AI used for:

operational decision support, e.g. asset and fleet management, workforce and workflow management

The goal is to build the most complete digital model, a "digital twin" of the healthcare enterprise and then use predictive analytics to generate possible outcomes and improve operational efficiency.

Operational decision support

Patient & hospital data for
consumer decision support

Data input:
longitudinal data on patients and enterprise-wide operational data

Analytics and AI used for:

assessment of patients’ needs

Algorithms could prompt or “nudge” lifestyle changes in the patient, or initiate conversation with the care provider in order to better manage—or even prevent—chronic conditions.

Read the case study: Using imaging and AI to help diagnose and manage COVID-19 patients

case study preview

This case study explores the potential of medical imaging with CTs or chest x-rays together with AI-assisted image interpretation in the diagnosis of COVID-19. Learn details about the machine learning needed to develop AI algorithms, data sharing initiatives and cross-institutional projects, all working towards a diagnostic support tool for COVID-19 based on medical imaging.


We are the global leader when it comes to AI patent applications in medical imaging and have been a pioneer in AI development for more than 20 years.