Streamlining Quality Review of Mass Spectrometry Data in the Clinical Laboratory by Use of Machine Learning.

Journal: Archives of pathology & laboratory medicine
Published Date: Aug 1, 2019

Abstract

CONTEXT.—: Turnaround time and productivity of clinical mass spectrometric (MS) testing are hampered by time-consuming manual review of the analytical quality of MS data before release of patient results.

Authors

  • Min Yu
    From the Division of Laboratory Medicine, Department of Pathology, University of Virginia School of Medicine and Health System, Charlottesville. Dr Yu is currently located in the Department of Pathology and Laboratory Medicine, University of Kentucky Medical Center, Lexington.
  • Lindsay A L Bazydlo
    From the Division of Laboratory Medicine, Department of Pathology, University of Virginia School of Medicine and Health System, Charlottesville. Dr Yu is currently located in the Department of Pathology and Laboratory Medicine, University of Kentucky Medical Center, Lexington.
  • David E Bruns
    From the Division of Laboratory Medicine, Department of Pathology, University of Virginia School of Medicine and Health System, Charlottesville. Dr Yu is currently located in the Department of Pathology and Laboratory Medicine, University of Kentucky Medical Center, Lexington.
  • James H Harrison
    From the Division of Laboratory Medicine, Department of Pathology, University of Virginia School of Medicine and Health System, Charlottesville. Dr Yu is currently located in the Department of Pathology and Laboratory Medicine, University of Kentucky Medical Center, Lexington.

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