A Machine Learning Approach for the Automated Interpretation of Plasma Amino Acid Profiles.

Journal: Clinical chemistry
Published Date:

Abstract

BACKGROUND: Plasma amino acid (PAA) profiles are used in routine clinical practice for the diagnosis and monitoring of inherited disorders of amino acid metabolism, organic acidemias, and urea cycle defects. Interpretation of PAA profiles is complex and requires substantial training and expertise to perform. Given previous demonstrations of the ability of machine learning (ML) algorithms to interpret complex clinical biochemistry data, we sought to determine if ML-derived classifiers could interpret PAA profiles with high predictive performance.

Authors

  • Edmund H Wilkes
    Department of Clinical Biochemistry, University College London Hospitals, London, UK.
  • Erin Emmett
    Biochemical Sciences, Viapath, Guys & St Thomas' NHS Foundation Trust, London, UK.
  • Luisa Beltran
    Biochemical Sciences, Viapath, Guys & St Thomas' NHS Foundation Trust, London, UK.
  • Gary M Woodward
    Department of Clinical Biochemistry, University College London Hospitals, London, UK. gary.woodward1@nhs.net.
  • Rachel S Carling
    Biochemical Sciences, Viapath, Guys & St Thomas' NHS Foundation Trust, London, UK.