Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence: Lessons Learned from Radiology
8
Zitationen
1
Autoren
2019
Jahr
Abstract
Artificial intelligence (AI) will continue to increase its significant impact on the everyday acquisition, interpretation, and application of data in our healthcare system. It is difficult to predict whether and to what extent AI will change the health status of patients, but it certainly will change the way decisions are made, how healthcare is delivered, and the ways providers, patients, and healthcare enterprises interact with and use data from an increasing array of sources. Radiology has often been at the forefront of technological change in healthcare and the AI revolution is no different. The lessons radiology has learned to date, its successes and challenges, can help provide guidance for other specialties, especially since radiology interacts with and cross-cuts nearly every other specialty and touches nearly every patient at least once in his or her lifetime.
Ähnliche Arbeiten
Refinement and reassessment of the SERVQUAL scale.
1991 · 3.966 Zit.
Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review
2005 · 3.755 Zit.
Radiobiology for the Radiologist.
1974 · 3.501 Zit.
International evidence-based recommendations for point-of-care lung ultrasound
2012 · 2.807 Zit.
Radiation Dose Associated With Common Computed Tomography Examinations and the Associated Lifetime Attributable Risk of Cancer
2009 · 2.426 Zit.