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1.
An experimental machine learning study investigating the decision-making process of students and qualified radiographers when interpreting radiographic images.
PLOS Digit Health
; 2(10): e0000229, 2023 Oct.
Artículo
en Inglés
| MEDLINE | ID: mdl-37878569
2.
An insight into the current perceptions of UK radiographers on the future impact of AI on the profession: A cross-sectional survey.
J Med Imaging Radiat Sci
; 53(3): 347-361, 2022 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-35715359
3.
An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice.
Health Technol (Berl)
; 11(5): 1045-1050, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-34377625
4.
Beauty Is in the AI of the Beholder: Are We Ready for the Clinical Integration of Artificial Intelligence in Radiography? An Exploratory Analysis of Perceived AI Knowledge, Skills, Confidence, and Education Perspectives of UK Radiographers.
Front Digit Health
; 3: 739327, 2021.
Artículo
en Inglés
| MEDLINE | ID: mdl-34859245
5.
Computing eye gaze metrics for the automatic assessment of radiographer performance during X-ray image interpretation.
Int J Med Inform
; 105: 11-21, 2017 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-28750903
6.
The accuracy of adult limb radiograph interpretation by emergency nurse practitioners: a prospective comparative study.
Int J Nurs Stud
; 52(1): 495-7, 2015 Jan.
Artículo
en Inglés
| MEDLINE | ID: mdl-24393763
7.
Additional comments to Richard Price on radiographer reporting in New Zealand.
Radiography (Lond)
; 13(1): 83-84, 2007 Feb.
Artículo
en Inglés
| MEDLINE | ID: mdl-33383607
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