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Motivation
Autoimmune diseases such as Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) are an increasing challenge for healthcare systems. These conditions often present with non-specific symptoms and frequently go undetected. The lack of reliable biomarkers and the diffuse nature of symptoms that affect multiple organ systems make early diagnosis and targeted treatment extremely difficult. There is an urgent need for innovative diagnostic tools that can improve early detection and enable more personalized treatment strategies for affected individuals.
Objectives
and approach
Our team aims to develop advanced diagnostic methods for complex diseases such as Long COVID and ME/CFS. Led by the Department of Rheumatology and Clinical Immunology at the University of Lübeck and the University Hospital Schleswig-Holstein (UKSH), we are leveraging AI and cell-based laboratory analyses to identify disease-specific immunological patterns. Using machine learning, we can analyze complex datasets to improve diagnostic accuracy, reduce the number of undiagnosed cases and facilitate individualized treatment decisions.
Our partners in this project are:
Innovations and perspectives
We combine cutting-edge laboratory techniques with AI-driven data analysis to simulate immunological processes outside the human body and detect characteristic disease patterns. Our innovative approach enables precise, patient-specific diagnostics and helps bridge the gap between fundamental research and clinical practice, contributing significantly to the advancement of precision medicine.
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