In the Netherlands (17.4 million inhabitants), almost 400.000 individuals live with the consequences of a stroke that affect their daily functioning due to problems with movement, cognition, and language. To minimize the consequences of a stroke, stroke patients must receive the right treatment from the right professional at the right time, both early post-stroke but also often in the months and years later.
In this Ph.D. position, you will investigate trajectories of stroke recovery with AI. This should enable data-driven individualized stroke rehabilitation and integrated stroke care pathways based on current patients' abilities and predicted stroke recovery. AI-based prognostic models should support clinical decision-making to select the right therapy to the right patient at the right time, amongst others focusing on 1) optimal patient discharge policies to home, nursing home, or rehabilitation center, and 2) optimal individualized rehabilitation treatment selection within the different treatment settings relevant to stroke patients (e.g., rehabilitation centers, nursing homes or first-line treatment such as physical therapy).
This PhD project is one of the five PhD positions in the ICAI Stroke Lab, one of the ROBUST program's labs. The ROBUST program on Trustworthy AI-based Systems adds 17 new labs to the
ICAI's current ecosystem.
The aim of the ICAI Stroke lab is to improve the outcome of stroke patients by optimizing the whole chain from the 112-call to rehabilitation with AI. Specifically, we intend to develop and assess AI-based patient stratification (faster, more accurate) for acute stroke care interventions, AI based functional outcome prediction after endovascular therapy, image-guidance in endovascular interventions for better therapeutic outcome and data-driven individualized stroke recovery policies, based on patients' current abilities and on constantly updated prognostic models for stroke recovery. In addition, we will study the acceptance of such AI-models by clinical decision-makers. There will be strong collaboration between the PhD students in the ICAI lab.