mHealth apps for gestational diabetes mellitus that provide clinical decision support or artificial intelligence: A scoping review.

Journal: Diabetic medicine : a journal of the British Diabetic Association
Published Date: Nov 16, 2021

Abstract

AIMS: Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. Mobile health (mHealth) applications (apps) are proposed for streamlining healthcare service delivery, extending care relationships into the community, and empowering those affected by prolonged medical disorders to be equal collaborators in their healthcare. This review investigates mHealth apps intended for use with GDM; specifically those powered by artificial intelligence (AI) or providing decision support.

Authors

  • Bridget J Daley
    Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK.
  • Michael Ni'Man
    Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK.
  • Mariana R Neves
    School of Electronic Engineering and Computer Science (EECS), Queen Mary University of London, London, United Kingdom.
  • Mohammed S Bobby Huda
  • William Marsh
    Risk and Information Management Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, Mile End Campus, Computer Science Building, E1 4NS London, UK.
  • Norman E Fenton
    Risk and Information Management, Queen Mary University of London, London, UK.
  • Graham A Hitman
    Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK.
  • Scott McLachlan
    School of Electronic Engineering and Computer Science (EECS), Queen Mary University of London, London, United Kingdom; Health Informatics and Knowledge Engineering Research (HiKER) Group.

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