Each year, more than 30,000 patients with ischemic stroke are admitted in a Dutch hospital and this number is increasing. Endovascular thrombectomy is a new treatment that was introduced in 2015 and strongly improves functional outcomes of stroke patients. However, major challenges remain. One of the most prominent is that despite a successful endovascular thrombectomy one to two thirds of patients still have a poor outcome. Moreover, further down the clinical management of stroke patients, identifying those individuals who benefit most from rehabilitation and providing patients with realistic outcome estimations are also of great importance. In this PhD project you will contribute to solving these challenges. You will analyse large clinical and radiolodical data sets to optimize endovascular therapy and rehabilitation trajectories based on pre- peri- and post-interventional parameters.
The 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.