Health data science

Theme description

By collecting and analysing data collected from everyday healthcare practice, and from population and clinical studies, Erasmus MC continually learns more about health and disease. Novel data processing and analysis methods, such as from the field of artificial intelligence, can make a huge difference.

TU Delft has much experience in this area. Together, we want to develop new data-driven health approaches. A health data science approach can help transform traditional healthcare into a proactive system, targeting health and prevention and using a life-course approach. To make this a reality, we will make use of (or build) new data collections such as biobanks, environmental data, data collected through wearable sensors and patient-reported data.

 

 
 

Flagship “My Digital Twin”

The Digital Twin is a technological framework to create a digital representation of an individual’s health and disease status, in a way that even allows predicting how specific aspects of this person’s health and disease will develop over time, as a function of different interventions for prevention and treatment.

 

To create this framework, we will

  1. collect data over the full life course
  2. develop tools and models to assess health and disease risk based on these data, and
  3. use the outcomes towards personalized and precise prevention and treatment.

 

Achievements

  • Precision prevention to improve health outcomes
  • Data-driven methods to select the optimal therapy for each individual patient
  • Personal biosensors to help people manage their own health
  • Disease Increased efficiency in healthcare to lower costs