Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

Journal: Clinical chemistry
Published Date: Nov 1, 2018

Abstract

BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of disorders of steroidogenesis and adrenal pathologies. Machine learning (ML) algorithms are powerful computational tools used extensively for the recognition of patterns in large data sets. Here, we investigated the utility of various ML algorithms for the automated biochemical interpretation of urine steroid profiles to support current clinical practices.

Authors

  • Edmund H Wilkes
    Department of Clinical Biochemistry, University College London Hospitals, London, UK.
  • Gill Rumsby
    Department of Clinical Biochemistry, University College London Hospitals, London, UK.
  • Gary M Woodward
    Department of Clinical Biochemistry, University College London Hospitals, London, UK. gary.woodward1@nhs.net.

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