In many of our projects, large collections of data emerge. Those 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 like 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 modular software platform, QuantMed. Our goal is to enable more reliable, accurate, and efficient clinical decisions. QuantMed offers support along the way: Creating the reference training data, training deep learning models, validating them, and deploying the results into your quantitative diagnostic software. Improving a model only requires experts to correct its predictions, and to update the training data collection. With QuantMed, partners in different institutions can extract medical knowledge together, but without pooling the sensitive patient data. QuantMed nodes in each institution locally extract knowledge into knowledge modules. The QuantMed hub collects the knowledge modules from the nodes, fuses them, and re-distributes 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, but all 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