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dc.contributor.authorSuleiman, M.E.en
dc.contributor.authorRickard, M.en
dc.contributor.authorBrennan, P.C.en
dc.date.accessioned2020-08-14
dc.date.available2020-08-14
dc.date.issued2020en
dc.identifier.urihttps://hdl.handle.net/2123/23076
dc.description.abstractIntroduction: Radiologists’ image reading skills vary, such variations in image interpretations can influence the effectiveness of the early treatment of disease and may have important clinical and economic implications. In screening mammography, clinical audits are used to assess radiologists’ performance annually, however, the nature of these audits prevent robust data analysis due to the low prevalence of breast cancer and the long waiting periods for the audit results. Research-based evidence revealed a need for changes in the methods utilised to optimise the assessment of the efficacy of radiologists’ interpretations. Methods: A cloud-based platform was developed to assess and enhance radiologists’ performance help reduce variability in medical image interpretations in a research environment; however, to address a number of limitations, the platform was commercialised to make it available worldwide. Results: DetectED-X’s team have been able to make their cloud-based platform available worldwide, tailored to the needs of radiologists and accredited for continuing medical/professional education; thus, changing the continuous professional development practice globally. Conclusion: DetectED-X’s Rivelato, was developed to address a need for effective, available and affordable educational solutions for clinicians and health care workers wherever they are located. A true fusion of industry, academia, clinics and consumer to adapt to the growing needs of clinicians’ around the world, the latest being COVID-19 global pandemic. DetectED-X repurposed its platform to educate physicians around the world on the appearances of COVID-19 on Lung Computed Tomography scans, introducing CovED to clinicians worldwide free of charge as a multi-national consortium of collaboration to help fight COVID-19, showing how research-based evidence can create effective and scalable change globally.en
dc.language.isoenen
dc.rightsOther
dc.subjectCOVID-19en
dc.subjectCoronavirusen
dc.titlePerfecting detection through educationen
dc.typeArticleen
dc.identifier.doi10.1016/j.radi.2020.06.006
usyd.facultyFaculty of Medicine and Health, Sydney Medical Schoolen


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