AI-Driven Compensation Matrix Refinement in Flow Cytometry

Recent improvements in flow cytometry data have spurred the emergence of sophisticated methodologies to handle the inherent challenges posed by spectral spillover. Traditionally, conventional compensation matrix development relies on single or multiple compensation controls, which can be prone to inaccuracies and introduce biases, particularly when

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