article Open AccessTop 10% cited
Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors
European Radiology · 2020 · Vol. 30(10) · pp. 5525–5532
L.G.D. Strohm(Utrecht University)Charisma Hehakaya✉(Utrecht University)Erik Ranschaert(Elisabeth-TweeSteden Ziekenhuis)Wouter Boon(Utrecht University)Ellen H.M. Moors(Utrecht University)
Abstract
• Successful implementation of AI in radiology requires collaboration between radiologists and referring clinicians. • Implementation of AI in radiology is facilitated by the presence of a local champion. • Evidence on the clinical added value of AI in radiology is needed for successful implementation.
Artificial Intelligence in Healthcare and EducationRadiology practices and educationAI in cancer detectionChampionMedicineInterventional radiologyAdded valueEarly adopterHealth careNeuroradiologyRadiologyKnowledge managementComputer science
MeSH terms
RadiologistsArtificial IntelligenceData CollectionHumansNetherlandsRadiographyRadiologyProgram EvaluationProgram DevelopmentQualitative Research
Citations
295
FWCI
8.12
field-weighted impact
References
40
Percentile
97%
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Citations per year
Cited by
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References
Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies
Journal of Medical Internet Research · 2017 · 2,470 citations
Artificial intelligence in radiology
Nature reviews. Cancer · 2018 · 3,504 citations
Medical students' attitude towards artificial intelligence: a multicentre survey
European Radiology · 2018 · 699 citations
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