Asthma is a chronic respiratory disease that affects more than 250 million people. It is a heterogeneous disease with a variety of symptoms, severity, and underlying mechanisms. Long term remission has been achieved for small subgroups of people with asthma treated with targeted biologic therapy. Accurately defining asthma subgroups is therefore of upmost importance for further reducing the prevalence of asthma. The rapid rise in technologies that enable profiling of a spectrum of analytes provides the opportunity to accurately classify asthma subtypes and to elucidate the underlying causes of disease. Combining these technologies with artificial intelligence will enable more accurate disease prediction, precision diagnoses, and personalised treatments. A major challenge is the prioritisation and effective implementation of these technologies in clinical practice.
Keywords: Artificial intelligence; Asthma; Biomarkers; Molecular biology; Proteomics.
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