ArticleEuropean journal of radiology open2024
Diagnostic performance with and without artificial intelligence assistance in real-world screening mammography.
Article in European journal of radiology open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Artificial intelligence in mammography: a systematic review of the external validation.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2024Pooled it
- Implementation of an artificial intelligence-based system for mammography in the compulsory medical insurance program: results of a 3-year study.Quantitative imaging in medicine and surgery · 2026Article
- Automated diagnosis of usual interstitial pneumonia on chest CT via the mean curvature of isophotes.European journal of radiology open · 2026Article
- Artificial intelligence in breast cancer screening: A systematic review and meta-analysis of integration strategies.European journal of radiology open · 2026Review
- Clinical Performance Tradeoffs of ChatGPT-5.2 Thinking (OpenAI) Compared with Radiologist Interpretation in Biopsy-Referred Mammography: Cancer Detection, False Positives, and Laterality.Tomography (Ann Arbor, Mich.) · 2026Article
- Adding artificial intelligence case malignancy scoring to reduce screen-reading workload in breast screening program: results of the retrospective REAI program.La Radiologia medica · 2026Article
- The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions.Journal of breast cancer · 2025Review
- AI-guided precision parenteral nutrition for neonatal intensive care units.Nature medicine · 2025Article
- Review
- Hybrid framework for automated generation of mammography radiology reports.Computational and structural biotechnology journal · 2025Article
- Enhancing patient outcomes: the role of clinical utility in guiding healthcare providers in curating radiology AI applications.Frontiers in digital health · 2024Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate artificial intelligence-based computer-aided diagnosis (AI-CAD) for screening mammography, we analyzed the diagnostic performance of radiologists by providing and withholding AI-CAD results alternatively every month. Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. Between August 2020 and May 2022, 1819 consecutive women (mean age 50.8 ± 9.4 years) with 2061 screening mammography and ultrasound performed on the same day in a single institution were included. Radiologists interpreted screening mammography in clinical practice with AI-CAD results being provided or withheld alternatively by month. The AI-CAD results were retrospectively obtained for analysis even when withheld from radiologists. The diagnostic performances of radiologists and stand-alone AI-CAD were compared and the performances of radiologists with and without AI-CAD assistance were also compared by cancer detection rate, recall rate, sensitivity, specificity, accuracy and area under the receiver-operating-characteristics curve (AUC). Results: Twenty-nine breast cancer patients and 1790 women without cancers were included. Diagnostic performances of the radiologists did not significantly differ with and without AI-CAD assistance. Radiologists with AI-CAD assistance showed the same sensitivity (76.5%) and similar specificity (92.3% vs 93.8%), AUC (0.844 vs 0.851), and recall rates (8.8% vs. 7.4%) compared to standalone AI-CAD. Radiologists without AI-CAD assistance showed lower specificity (91.9% vs 94.6%) and accuracy (91.5% vs 94.1%) and higher recall rates (8.6% vs 5.9%, all p < 0.05) compared to stand-alone AI-CAD. Conclusion: Radiologists showed no significant difference in diagnostic performance when both screening mammography and ultrasound were performed with or without AI-CAD assistance for mammography. However, without AI-CAD assistance, radiologists showed lower specificity and accuracy and higher recall rates compared to stand-alone AI-CAD.
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