Selected article for: "artificial intelligence and information technology"

Author: Huang, Fanyu; Brouqui, Philippe; Boudjema, Sophia
Title: How does innovative technology impact nursing in infectious diseases and infection control? A scoping review
  • Cord-id: 97leq7n2
  • Document date: 2021_3_25
  • ID: 97leq7n2
    Snippet: AIM: Considering the increasing number of emerging infectious diseases, innovative approaches are strongly in demand. Additionally, research in this field has expanded exponentially. Thus, faced with this diverse information, we aim to clarify key concepts and knowledge gaps of technology in nursing and the field of infectious diseases. DESIGN: This scoping review followed the methodology of scoping review guidance from Arksey and O’Malley. METHODS: Six databases were searched systematically (
    Document: AIM: Considering the increasing number of emerging infectious diseases, innovative approaches are strongly in demand. Additionally, research in this field has expanded exponentially. Thus, faced with this diverse information, we aim to clarify key concepts and knowledge gaps of technology in nursing and the field of infectious diseases. DESIGN: This scoping review followed the methodology of scoping review guidance from Arksey and O’Malley. METHODS: Six databases were searched systematically (PubMed, Web of Science, IEEE Explore, EBSCOhost, Cochrane Library and Summon). After the removal of duplicates, 532 citations were retrieved and 77 were included in the analysis. RESULTS: We identified five major trends in technology for nursing and infectious diseases: artificial intelligence, the Internet of things, information and communications technology, simulation technology and e‐learning. Our findings indicate that the most promising trend is the IoT because of the many positive effects validated in most of the reviewed studies.

    Search related documents:
    Co phrase search for related documents
    • abstract title screening and machine learning: 1, 2, 3, 4, 5, 6
    • low participation and machine learning: 1