Danni Tu, Bridget Mahony, Tyler M Moore, Maxwell A Bertolero, Aaron F Alexander-Bloch, Ruben Gur, Dani S Bassett, Theodore D Satterthwaite, Armin Raznahan, Russell T Shinohara
CoCoA: conditional correlation models with association size
Biostatistics (Oxford, England)
medical imaging arguably technologically advanced field healthcare encompassing range technologies continually evolve computing power human knowledge expand artificial intelligence ai next frontier medical imaging pioneering rapid development implementation ai potential revolutionise healthcare however staff must competent confident application hence ai readiness important precursor ai adoption research ascertain best way deliver aienabled healthcare training infancy aim scoping review compare existing studies investigate evaluate efficacy ai educational interventions medical imaging staff following creation search strategy keyword searches screening conducted determine study eligibility consisted title abstract scan subsequently fulltext review articles included empirical studies wherein educational intervention ai medical imaging staff created delivered evaluated initial 1309 records returned n 5 04 studies met eligibility criteria review curricula delivery five studies shared similar aims flipped classroom delivery utilised method however depth content covered curricula varied measured outcomes differed greatly findings review provide insights evaluation existing ai educational interventions valuable planning ai education healthcare staff review highlights need standardised comprehensive ai training programs imaging staff