Multi-parameter flow cytometry is a powerful analytical tool, enabling rapid measurement of multiple, physical and chemical characteristics of individual cells. Examples of clinical applications of flow cytometry analysis are the measurement of minimal residual disease (MRD) in leukemia, inflammatory disease and the effect of biologicals. While flow cytometry has become more advanced, the interpretation of information is still complicated and time consuming for clinicians, technicians and researchers. Radboud University Nijmegen, together with UMC Utrecht, has developed an algorithm able to process raw data and filter disease-specific outcomes, by comparing the patient data with a healthy population, making diagnosis easier and faster. Moreover, increased precision means the number of false negatives will be reduced, allowing for an early cancer intervention.
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