Self-supervised Learning for Tumor Microenvironment Analysis: Addressing Label Scarcity in Multiplexed Immunofluorescence Imaging with Novel Feature Extraction Techniques

The study of tumor microenvironments (TMEs) and immune cell composition in cancer, a disease characterized by uncontrolled growth and spread of tumor cells, has become increasingly important for understanding tumor progression and patient outcomes. Tools such as the TME-Analyzer enable this kind of research, but their manual workflows highlight...

Digging through the dirt: a general method for abstract discrete state estimation with limited prior knowledge

Autonomous robots are often successfully deployed in controlled environments. Operation in uncontrolled situations remains challenging; it is hypothesized that the detection of abstract discrete states (ADS) can improve operation in these circumstances. ADS are high-level system states that are not directly detectable and influence system...

Global shoreline forecasting with a clustering approach

Coastal areas around the world have always been densely populated areas. However, sea-level-rise and an increase in single extreme events due to climate change, threaten the coastal areas and their inhabitants. Governmental organizations, coastal managers and various private parties thrive for better insights into long-term shoreline behavior...

Interpretable Machine Learning for Biomarker Discovery in Imaging Mass Spectrometry Data

Imaging mass spectrometry (IMS) is a multiplexed chemical imaging technique that enables the spatially targeted molecular mapping of biological samples at cellular resolutions. Within a single experiment, IMS can measure the spatial distribution and relative concentration of thousands of distinct molecular species across the surface of a tissue...

On domain-adaptive machine learning

Artificial intelligence, and in particular machine learning, is concerned with teaching computer systems to perform tasks. Tasks such as autonomous driving, recognizing tumors in medical images, or detecting suspicious packages in airports. Such systems learn by observing examples, i.e. data, and forming a mathematical description of what types...