Machine learning for classification of hypertension subtypes using multi-omics: A multi-centre, retrospective, data-driven study

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• Finished

  Omics-Based Strategies for Improved Diagnosis and Treatment of Endocrine Hypertension (ENSAT-HT) (Joint with Inserm, University of Torino, University of Padua, University of Glasgow, University of Birmingham, Radboud University Medical Centre, SleekIT Limited and Inserm Transfert)

  Connell, J. (Investigator), Doney, A. (Investigator), Jefferson, E. (Investigator) & Zhou, K. (Investigator)

  COMMISSION OF THE EUROPEAN COMMUNITIES

  1/05/15 → 31/12/21

  Project: Research

  • Endocrine Hypertension 100%
  • Primary Hypertension 88%
  • Machine Learning 64%
  • Hypertension Subtypes 55%
  • Cushing's Syndrome 52%