PallMAB (Palliative Care and Multimodal Analysis of Biomarkers)
PallMAB – Introduction
PallMAB (Palliative Care and Multimodal Analysis of Biomarkers) is a research initiative dedicated to advancing palliative care through the integrated analysis of multimodal health data. The group combines high-resolution physiological sensing, biomaterial-derived markers, and routinely collected clinical data to better understand and predict patient-relevant outcomes.
Using a broad spectrum of technologies—including contactless radar systems, wearable devices, smart patches, and digital health infrastructures—PallMAB captures continuous, real-world physiological signals. These data are complemented by biomolecular information from biobanking as well as structured and unstructured data from electronic health records.
A central focus lies in the development and application of advanced analytical approaches, ranging from classical statistical methods to machine learning and artificial intelligence. By integrating heterogeneous data sources, PallMAB aims to model complex clinical trajectories and identify meaningful patterns in symptom burden, functional status, and disease progression.
The overarching goal is to enable more precise, data-driven, and patient-centered care in palliative medicine—supporting clinical decision-making, improving symptom management, and contributing to a deeper understanding of the needs of patients with severe and life-limiting illness.
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