ArticleCancer imaging : the official publication of the International Cancer Imaging Society2023
Breast cancer detection accuracy of AI in an entire screening population: a retrospective, multicentre study.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2023. 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.
- 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
- Ten Years of Artificial Intelligence in Screening Mammography: A Systematic Review and Meta-Analysis of Diagnostic Accuracy and Clinical Implementation (Literature Published 2015-2025).Diagnostics (Basel, Switzerland) · 2026Review
- Application of Artificial Intelligence in Breast Ultrasound Diagnosis.Diagnostics (Basel, Switzerland) · 2026Review
- Artificial intelligence in breast cancer screening: A systematic review and meta-analysis of integration strategies.European journal of radiology open · 2026Review
- Bridging Pixels and Practice: AI-Assisted Mammography as a Next-Generation Diagnostic Strategy for Breast Cancer Screening.Diagnostics (Basel, Switzerland) · 2026Review
- Retrospective evaluation of interval breast cancer screening mammograms by radiologists and AI.European radiology · 2026Article
- Improving Benign and Malignant Classifications in Mammography with ROI-Stratified Deep Learning.Bioengineering (Basel, Switzerland) · 2025Article
- Influence of AI Decision Support on Radiologists' Performance and Visual Search in Screening Mammography.Radiology · 2025Article
- AI-CAD-Guided Mammographic Assessment of Tumor Size and T Stage: Concordance with MRI for Clinical Staging in Breast Cancer Patients Considered for NAC.Tomography (Ann Arbor, Mich.) · 2025Article
- AI-integrated Screening to Replace Double Reading of Mammograms: A Population-wide Accuracy and Feasibility Study.Radiology. Artificial intelligence · 2024Article
- Artificial intelligence-assisted detection of challenging ischemic stroke on diffusion-weighted imaging: a reader study.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) systems are proposed as a replacement of the first reader in double reading within mammography screening. We aimed to assess cancer detection accuracy of an AI system in a Danish screening population.
methodsWe retrieved a consecutive screening cohort from the Region of Southern Denmark including all participating women between Aug 4, 2014, and August 15, 2018. Screening mammograms were processed by a commercial AI system and detection accuracy was evaluated in two scenarios, Standalone AI and AI-integrated screening replacing first reader, with first reader and double reading with arbitration (combined reading) as comparators, respectively. Two AI-score cut-off points were applied by matching at mean first reader sensitivity (AI
resultsOut of 272,008 screening mammograms from 158,732 women, 257,671 (94.7%) with adequate image data were included in the final analyses. Sensitivity and specificity were 63.7% (95% CI 61.6%-65.8%) and 97.8% (97.7-97.8%) for first reader, and 73.9% (72.0-75.8%) and 97.9% (97.9-98.0%) for combined reading, respectively. Standalone AI
conclusionsReplacing first reader in double reading with an AI could be feasible but choosing an appropriate AI threshold is crucial to maintaining cancer detection accuracy and workload.
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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.