ArticleEuropean radiology2010
Using computer-aided detection in mammography as a decision support.
Article in European radiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.
- Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review.JAMA network open · 2021Pooled it
- Greater benefits of deep learning-based computer-aided detection systems for finding small signals in 3D volumetric medical images.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Framing the fallibility of Computer-Aided Detection aids cancer detection.Cognitive research: principles and implications · 2023Article
- A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis.Open life sciences · 2022Review
- WHAT CAN WE ACTUALLY SEE USING COMPUTER AIDED DETECTION IN MAMMOGRAPHY?Acta clinica Croatica · 2020Article
- Deep feature-based automatic classification of mammograms.Medical & biological engineering & computing · 2020Article
- Is there a safety-net effect with computer-aided detection?Journal of medical imaging (Bellingham, Wash.) · 2020Article
- AI-based computer-aided diagnosis (AI-CAD): the latest review to read first.Radiological physics and technology · 2020Review
- Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software.Acta radiologica (Stockholm, Sweden : 1987) · 2020Article
- Augmented Radiologist Workflow Improves Report Value and Saves Time: A Potential Model for Implementation of Artificial Intelligence.Academic radiology · 2020Article
- Article
- Clinical Translation of the LevelCheck Decision Support Algorithm for Target Localization in Spine Surgery.Annals of biomedical engineering · 2018Article
- Focal breast lesion characterization according to the BI-RADS US lexicon: role of a computer-aided decision-making support.La Radiologia medica · 2018Article
- Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.Attention, perception & psychophysics · 2017Article
- Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions.Physics in medicine and biology · 2017Article
- A new approach to develop computer-aided detection schemes of digital mammograms.Physics in medicine and biology · 2015Article
- Who could benefit the most from using a computer-aided detection system in full-field digital mammography?World journal of surgical oncology · 2014Article
- New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs.The British journal of radiology · 2014Observational
- Article
- A modified undecimated discrete wavelet transform based approach to mammographic image denoising.Journal of digital imaging · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate an interactive computer-aided detection (CAD) system for reading mammograms to improve decision making.
methodsA dedicated mammographic workstation has been developed in which readers can probe image locations for the presence of CAD information. If present, CAD findings are displayed with the computed malignancy rating. A reader study was conducted in which four screening radiologists and five non-radiologists participated to study the effect of this system on detection performance. The participants read 120 cases of which 40 cases had a malignant mass that was missed at the original screening. The readers read each mammogram both with and without CAD in separate sessions. Each reader reported localized findings and assigned a malignancy score per finding. Mean sensitivity was computed in an interval of false-positive fractions less than 10%.
resultsMean sensitivity was 25.1% in the sessions without CAD and 34.8% in the CAD-assisted sessions. The increase in detection performance was significant (p = 0.012). Average reading time was 84.7 ± 61.5 s/case in the unaided sessions and was not significantly higher when interactive CAD was used (85.9 ± 57.8 s/case).
conclusionInteractive use of CAD in mammography may be more effective than traditional CAD for improving mass detection without affecting reading time.
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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.