Many of our projects produce large collections of data. These big data sets stem from population-based studies, interdisciplinary clinical research projects, or from freely available crowd challenges. Using state-of-the-art machine learning techniques such as convolutional neural networks and other deep learning architectures, we explore the wealth of information contained in this clinical data.
Preparing your data – Training your AI – Building your solution
We support quantitative medicine with our QuantMed modular software platform. Our goal is to enable more reliable, accurate, and efficient clinical decisions. QuantMed offers support along the way: creating reference training data, training and validating deep learning models, and deploying the results into your quantitative diagnostic software. Improving a model requires experts only to correct its predictions and to update the training data collection. With QuantMed, partners at different institutions can extract medical knowledge together without pooling sensitive patient data. QuantMed nodes at each institution locally extract knowledge into knowledge modules. The QuantMed hub collects the knowledge modules from the nodes, fuses them, and redistributes the update to the nodes. Knowledge modules are safe to share under data protection regulations. They do not contain any patient or institution-specific data, only the required technical information to use them in AI products.
We offer end-to-end support for translational research. Your idea, your data, your envisioned solution – our modular toolchain connects the dots
QuantMed offers extended annotation capabilities for training your data
Systematic generation, accumulation, validation, and utilization of quantifiable medical knowledge
Full integration with MeVisLab for building your software solution