Clinical Data Science

Radiological Computer Vision: Applying established machine-learning-based computer vision techniques for radiological diagnosis and prognosis

Biostatistics: Applying statistical methods to analyze and interpret complex clinical data with statistical rigorosity

Applied LLMs: Using large language models to process and understand numerous aspects of clinical text data

Multimodal DL: Integrating various data types (imaging, text, etc.) to enhance the accuracy and applicability of our AI models

Image analysis of PET/CT: We are organizers of the AutoPET Challenge series, which focuses on segmentation of pathological tracer uptake in hybrid imaging.

High Performance Computing (HPC): We maintain the clinical HPC core facility CORE - for heavy CPU and GPU workloads. Our computing enviornment enables local deployment of state-of-the-art machine learning models.

Clinical LLM: Developing language models tailored for clinical data analysis.

Reliable AI: Clinical AI applications require careful evaluation with a strong focus on reliability, explainability and trustworthiness - does the model predict the right thing for the right reasons?

Federated Learning (RACOON, BORN): We contribute to collaborative multi-centric radiology frameworks that enable clinical machine learning and ensure data privacy and security.

We are an interdisciplinary research group for clinical data science in radiology. Our mission is to advance clinical data science to improve patient outcomes by leveraging cutting-edge AI technologies, including computer vision, applied large language models (LLMs), and multimodal deep learning (DL). Our diverse team, including specialists from physics, statistics, computer science, and various clinical fields, collaborates closely with radiologists to create innovative solutions for real-world healthcare challenges.

Are you a PhD candidate in biostatistics or computer science? Do you want to be part of a dynamic, interdisciplinary team that's shaping the future of clinical data science? We invite you to explore the opportunities we offer. Here, you will work on impactful projects, engage with real clinical data, and contribute to the development of AI tools that are reliable, explainable, and trustworthy.