Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside.

Journal: Annals of the Academy of Medicine, Singapore
PMID: 38904533

Abstract

Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural language processing in medical chatbots and electronic medical record extraction have the potential to improve screening, diagnostics and prognostication, leading to precision medicine and preventive health. However, it is crucial to ensure that AI research is conducted with scientific rigour to facilitate clinical implementation. Therefore, reporting guidelines have been developed to standardise and streamline the development and validation of AI technologies in health. This commentary proposes a structured approach to utilise these reporting guidelines for the translation of promising AI techniques from research and development into clinical translation, and eventual widespread implementation from bench to bedside.

Authors

  • Zhen Ling Teo
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Ann Kwee
    Department of Endocrinology, Singapore General Hospital, Singapore.
  • John Cw Lim
    Centre of Regulatory Excellence, Duke-NUS Medical School, National University of Singapore, Singapore.
  • Carolyn Sp Lam
    Department of Cardiology, National Heart Centre Singapore, Singapore.
  • Dean Ho
    The N.1 Institute for Health (N.1), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore.
  • Sebastian Maurer-Stroh
  • Yi Su
    Department of Gastroenterology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Simon Chesterman
    Faculty of Law, National University of Singapore, Singapore.
  • Tsuhan Chen
    AI Singapore, Singapore.
  • Chorh Chuan Tan
    Chief Health Scientist Office, Ministry of Health, Singapore.
  • Tien Yin Wong
    Singapore National Eye Center, Duke-National University of Singapore Medical School, Singapore 168751, Singapore; National Institutes of Health Research Biomedical Research Centre Biomedical Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
  • Kee Yuan Ngiam
    Group Chief Technology Office, National University Health System Singapore, Singapore, Singapore.
  • Cher Heng Tan
    Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore, Singapore.
  • Danny Soon
    Lilly-NUS, Singapore, Singapore.
  • May Ling Choong
    Health Sciences Authority, Singapore.
  • Raymond Chua
    McGill University and Mila, Montréal, Canada.
  • Sutowo Wong
    Data Analytics, Ministry of Health, Singapore.
  • Colin Lim
    Technology, Ministry of Health, Singapore.
  • Wei Yang Cheong
    Technology, Ministry of Health, Singapore.
  • Daniel Sw Ting
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.

Keywords

External Resources

Popular Topics
Recent Journals