Living a healthier life and at the same time managing the overall cost of healthcare provisioning. Artificial intelligence can contribute in many ways to this target: precision medicine, personalized treatments, predictive and preventive care, development of new medicines. 

Visual of how AI could be incorporated in a medical environment

Several demonstrators are being developed in this domain.

1. Within the precision medicine, the search for the best preventive care and optimization of treatments for patients is ongoing. High-dimensional data sets are being analyzed, with both genetic and contextual parameters of the individuals involved being gathered. This involves the integration of several data types and of the relevant domain expertise.

2. Clinical decision-making involves making the correct diagnosis and defining the best (personalized) treatment for patients. Therefore, the need for interpretable and actionable AI-based insights is crucial. One of the key challenges is the combination of several data types, resulting from different sources such as sensor data, imaging data, lab data, etc.

3. Within the decision support tools for hospitals, we implement AI in order to optimize the patient flows and ensure maximum use of available resources.

4. Due to the increased use of personal devices and applications for monitoring our own lifestyle or tracking specific body parameters, personal health data will become abundantly available. Determining how to make maximum use of this wealth of data in a correct and optimal way is a major challenge.

Precision medicine

Single-cell technologies

Treatment of patients with Multiple Sclerose (MS)

Clinical decision making

Medical image processing

Automatic epileptic seizure detection at home

Hospital decision making

Optimal patient flow and a prediction of the Length-of-Stay

Management of personal health data