Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating the Quality and Understandability of Radiology Report Summaries Generated by ChatGPT: Survey Study
5
Zitationen
8
Autoren
2025
Jahr
Abstract
ChatGPT-generated summaries could significantly improve perceived comprehension and satisfaction while accurately reflecting most key information from original radiology reports. Instances of minor omissions and under-/overemphasis were noted in some summaries, underscoring the need for ongoing validation and oversight. Overall, these artificial intelligence-generated, patient-centric summaries hold promise for enhancing patient-centered communication in radiology.
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 · 3.765 Zit.
Radiobiology for the Radiologist.
1974 · 3.501 Zit.
International evidence-based recommendations for point-of-care lung ultrasound
2012 · 2.810 Zit.
Radiation Dose Associated With Common Computed Tomography Examinations and the Associated Lifetime Attributable Risk of Cancer
2009 · 2.430 Zit.