Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Today’s radiologists meet tomorrow’s AI: the promises, pitfalls, and unbridled potential
12
Zitationen
6
Autoren
2021
Jahr
Abstract
Advances in information technology have improved radiologists' abilities to perform an increasing variety of targeted diagnostic exams. However, due to a growing demand for imaging from an aging population, the number of exams could soon exceed the number of radiologists available to read them. However, artificial intelligence has recently resounding success in several case studies involving the interpretation of radiologic exams. As such, the integration of AI with standard diagnostic imaging practices to revolutionize medical care has been proposed, with the ultimate goal being the replacement of human radiologists with AI 'radiologists'. However, the complexity of medical tasks is often underestimated, and many proponents are oblivious to the limitations of AI algorithms. In this paper, we review the hype surrounding AI in medical imaging and the changing opinions over the years, ultimately describing AI's shortcomings. Nonetheless, we believe that AI has the potential to assist radiologists. Therefore, we discuss ways AI can increase a radiologist's efficiency by integrating it into the standard workflow.
Ähnliche Arbeiten
Refinement and reassessment of the SERVQUAL scale.
1991 · 3.967 Zit.
Radiobiology for the Radiologist.
1974 · 3.502 Zit.
ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee
2017 · 2.432 Zit.
Accuracy of Physician Self-assessment Compared With Observed Measures of Competence
2006 · 2.326 Zit.
Technology as an Occasion for Structuring: Evidence from Observations of CT Scanners and the Social Order of Radiology Departments
1986 · 2.251 Zit.