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Machine Learning In Flow Cytometry For Acute Myeloid Leukemia Diagnosis: A Scoping Review, Katrina Jezzela M. Dela Pena Md, Mls (Ascp)

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Introduction: Flow cytometry is essential for the diagnosis of acute myeloid leukemia (AML), but conventional analysis is labor-intensive, operator-dependent, and increasingly complex. Machine learning (ML) may support automated analysis; however, its readiness for clinical implementation remains unclear. This scoping review mapped ML approaches applied to flow cytometry for AML-related diagnosis.

Methods: PubMed was searched for English-language primary studies applying artificial intelligence, ML, or deep learning to human flow cytometry data for AML diagnosis or classification. Eligible studies reported diagnostic performance metrics. Study characteristics, preprocessing, data representation, model architecture, validation strategy, performance metrics, interpretability, and implementation considerations were descriptively …