Digital health and artificial intelligence in kidney research: a report from the 2020 Kidney Disease Clinical Trialists (KDCT) meeting.
Fiche publication
Date publication
novembre 2021
Journal
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Auteurs
Membres identifiés du Cancéropôle Est :
Pr ROSSIGNOL Patrick
Tous les auteurs :
Yi TW, Laing C, Kretzler M, Nkulikiyinka R, Legrand M, Jardine M, Rossignol P, Smyth B
Lien Pubmed
Résumé
The exponential growth in digital technology coupled with the global COVID-19 pandemic is driving a profound change in the delivery of medical care and research conduct. The growing availability of electronic monitoring, electronic health records, smartphones and other devices, and access to ever greater computational power, provides new opportunities, but also new challenges. Artificial intelligence (AI) exemplifies the potential of this digital revolution, which also includes other tools such as mobile health (mHealth) services and wearables. Despite digital technology becoming commonplace, its use in medicine and medical research is still in its infancy, with many clinicians and researchers having limited experience with such tools in their usual practice. This paper, derived from the 'Digital Health and Artificial Intelligence' session of the Kidney Disease Clinical Trialists virtual workshop held in September 2020, aims to illustrate the breadth of applications to which digital tools and AI can be applied in clinical medicine and research. It highlights several innovative projects incorporating digital technology that range from streamlining medical care of those with acute kidney injury to the use of AI to navigate the vast genomic and proteomic data gathered in kidney disease. Important considerations relating to any new digital health project are presented, with a view to encouraging the further evolution and refinement of these new tools in a manner that fosters collaboration and the generation of robust evidence.
Mots clés
artificial intelligence, clinical trial, digital health, machine learning, prediction model
Référence
Nephrol Dial Transplant. 2021 Nov 13;: