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Laboratory Medicine|June 13, 2025
Performance metrics for machine learning solutions in laboratory medicineNicholas C Spies, David P NgCytometry. Part B, Clinical Cytometry|June 15, 2026
DinoFlow: Self-supervised pretraining in flow cytometry enables accurate detection of common hematopathological disordersBrendan O'Fallon, Muir Morrison, Mattia Medina Grespan, et al.Cancers|February 13, 2025
Machine Learning Methods in Clinical Flow CytometryNicholas C Spies, Alexandra Rangel, Paul English, et al.The Journal of Applied Laboratory Medicine|January 7, 2023
Data-Driven Anomaly Detection in Laboratory Medicine: Past, Present, and FutureNicholas C Spies, Christopher W Farnsworth, Ronald JackupsDiagnostic Cytopathology|June 3, 2024
Process improvement in thyroid fine needle aspiration: Standardizing number of smears for enhanced adequacy and diagnosisPatrick Morse, Kaleigh F Roberts, Nicholas C Spies, et al.International Journal of Laboratory Hematology|July 21, 2021
Flow cytometric myeloma measurable residual disease testing in the era of targeted therapiesDavid P NgClinical Chemistry|September 10, 2024
Validating, Implementing, and Monitoring Machine Learning Solutions in the Clinical Laboratory Safely and EffectivelyNicholas C Spies, Christopher W Farnsworth, Sarah Wheeler, et al.Critical Reviews in Clinical Laboratory Sciences|June 11, 2025
Machine learning-based error detection in the clinical laboratory: a critical reviewYanchun Lin, Isaiah K Mensah, Michelle Doering, et al.Plos Computational Biology|August 7, 2015
Informatics for RNA Sequencing: A Web Resource for Analysis on the CloudMalachi Griffith, Jason R Walker, Nicholas C Spies, et al.American Journal of Clinical Pathology|November 19, 2020
Augmented Human Intelligence and Automated Diagnosis in Flow Cytometry for Hematologic MalignanciesDavid P Ng, Lauren M ZuromskiPageof 5