We are excited to present our latest scientific paper in the renowned Journal of Allergy and Clinical Immunology (JACI). The research team at the Vienna Airway Lab of the Department of Otolaryngology, Head and Neck Surgery used modern methods to examine the entirety of proteins in nasal and blood samples - an approach known as proteomics - and evaluated this data using artificial intelligence. The goal was to better understand and classify different forms of chronic rhinosinusitis (CRS) - a complex inflammation of the sinuses.
During the process, we were able to identify new protein patterns and potential biomarkers that help distinguish patients with nasal polyps from CRS patients without polyps and from healthy individuals. With the help of machine learning, characteristic patterns were discovered that could support the development of improved diagnostic and treatment procedures in the future.
To make our research accessible to a wider audience, we results in a comic version, illustrated by Sara Miranda - science explained in a different way!
→ Click here to read: Proteomic profiling and machine learning for endotype prediction in chronic rhinosinusitis - Journal of Allergy and Clinical Immunology