Identifying cancer-associated leukocyte profiles using high-resolution flow cytometry screening and machine learning
David A. Simon Davis,
Melissa Ritchie,
Dillon Hammill
et al.
Abstract:BackgroundMachine learning (ML) is a valuable tool with the potential to aid clinical decision making. Adoption of ML to this end requires data that reliably correlates with the clinical outcome of interest; the advantage of ML is that it can model these correlations from complex multiparameter data sets that can be difficult to interpret conventionally. While currently available clinical data can be used in ML for this purpose, there exists the potential to discover new “biomarkers” that will enhance the effe… Show more
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