ArticleRadiography (London, England : 1995)2020
Perfecting detection through education.
Article in Radiography (London, England : 1995), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult.Journal of imaging informatics in medicine · 2025Article
- Review
- Optimizing mammography interpretation education: leveraging deep learning for cohort-specific error detection to enhance radiologist training.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Test-set results can predict participants' development in breast-screen cancer detection: An observational cohort study.Health science reports · 2024Article
- Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases.Journal of digital imaging · 2023Article
- Look how far we have come: BREAST cancer detection education on the international stage.Frontiers in oncology · 2022Review
- Translating radiography research into practice.Radiography (London, England : 1995) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionRadiologists' 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.
methodsA 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.
resultsDetectED-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.
conclusionDetectED-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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.