AI for precision medicine in stroke.
Our innovative simulation model enables predictive diagnostics in stroke treatment using digital medical imaging. We process patient-specific MRI and CT images with state-of-the art processing-tools and convolutional neural nets. This information is fed to our unique simulation that allows the estimation of cerebral perfusion changes under different conditions.
The simulation results together with routine clinical data allow predictive modelling for stroke risk and outcome using innovative machine learning techniques. Our approach will lead to personalized simulation of therapy options in stroke enabling patient-centered treatment and personalized risk assessment.
Each year more than 1.2 million people suffer from stroke in Europe alone. 15% of which have a re-stroke within a year.
Prevention strategies and clinical treatment of stroke are based on generalized guidelines and empirical data alone. No personalized diagnostics and treatment strategies are available. Digital opportunities are not exploited sufficiently.
With our AI solution we will save lives of stroke patients by personalizing stroke prevention and treatment utilizing high-precision imaging and unique Machine Learning approaches.
Avoid interventions where possible. Perform minimal therapy when necessary.
For validation of the product we are using high-quality international, multi-center clinical data.
Patient clinical data, simulation results and treatment information are used to feed state-of-the-art machine learning algorithms to calculate stroke risks, to predict patient outcome and risk of recurring stroke. We study the impact of our clinical AI solution on recommended treatment strategies and examine, if subsequent strokes can be mitigated when our software is used.
Risk prediction and therapy planning will be dramatically improved using our Stroke Risk Scores.
Treatment options will be provided in transparent reports including risk maps and detailed simulation results. The risk profile of competing treatment options can be quantified and compared. Relevant neurologic features and associated risk factors are visualized using individual patient imaging.
Unlike in competitive approaches only routine and standard medical imaging is required for successful simulations and data processing. No additional cost, time or patient involvement is necessary.
For automated image post-processing by convolutional neural nets we use high-precision imaging to allow unprecedented processing speed for real time analysis in the clinical setting.
Our innovative approach will help patients receive the best treatment.
Treatment decisions are based on patients and their relevant medical indications.
Reports allow transparent feedback on the risk factors and treatment options and empower the patient for informed consent.
Software-based prediction and simulation are performed without additional procedures.
Developed at one of the world's top medical research institutions.
Our predictive model and simulation component is implemented in a working prototype.
No requirement on input other than what is routinely gathered in a stroke event.