ArticleNature medicine2023
Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer.
Article in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 3 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
66 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- ESR Essentials: artificial intelligence in breast imaging-practice recommendations by the European Society of Breast Imaging.European radiology · 2026Guideline
- Artificial intelligence for glaucoma.The Cochrane database of systematic reviews · 2025Pooled it
- Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: Systematic Review and Framework for Safe Adoption.Journal of medical Internet research · 2025Pooled it
- Response to letter regarding "artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study".Annals of medicine · 2026Article
- Human-AI interaction and collaboration in radiology: from conceptual frameworks to responsible implementation.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Review
- AI Adoption in US Cancer Centers: National Cross-Sectional Study of Institutional and Policy Determinants.Journal of medical Internet research · 2026Article
- Artificial intelligence advances in cystoscopy and imaging for bladder cancer: a narrative review.The Canadian journal of urology · 2026Review
- Application of Artificial Intelligence in Breast Ultrasound Diagnosis.Diagnostics (Basel, Switzerland) · 2026Review
- Article
- AI software as a third reader in breast cancer screening-a prospective diagnostic observational study.European radiology · 2026Observational
- An evaluation of artificial intelligence assisted prostate biopsy reporting in the Articulate Pro study.NPJ digital medicine · 2026Article
- Artificial intelligence model boosts lung nodule diagnostic accuracy in clinical trial.Nature cancer · 2026Article
- Warning people about the risk of AI error mitigates human acquisition of AI bias.Cognitive research: principles and implications · 2026Article
- An ethics-informed computable audit framework for monitoring misdiagnosis risk in AI-assisted diagnosis.Scientific reports · 2026Article
- AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.Nature medicine · 2026Article
- Prospective evaluation of artificial intelligence integration into breast cancer screening in multiple workflow settings: the GEMINI study.Nature cancer · 2026Article
- A multi-scale hybrid ResNet-transformer with distance-aware learning for interpretable BI-RADS mammographic classification.Scientific reports · 2026Article
- An interpretable AI system reduces false-positive MRI diagnoses by stratifying high-risk breast lesions.Nature communications · 2026Article
- Artificial intelligence for breast cancer management.Communications medicine · 2026Review
- Artificial intelligence in cardio-oncology: decoding mechanisms, predicting toxicity, and personalizing cancer therapy.Frontiers in cardiovascular medicine · 2026Review
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has the potential to improve breast cancer screening; however, prospective evidence of the safe implementation of AI into real clinical practice is limited. A commercially available AI system was implemented as an additional reader to standard double reading to flag cases for further arbitration review among screened women. Performance was assessed prospectively in three phases: a single-center pilot rollout, a wider multicenter pilot rollout and a full live rollout. The results showed that, compared to double reading, implementing the AI-assisted additional-reader process could achieve 0.7-1.6 additional cancer detection per 1,000 cases, with 0.16-0.30% additional recalls, 0-0.23% unnecessary recalls and a 0.1-1.9% increase in positive predictive value (PPV) after 7-11% additional human reads of AI-flagged cases (equating to 4-6% additional overall reading workload). The majority of cancerous cases detected by the AI-assisted additional-reader process were invasive (83.3%) and small-sized (≤10 mm, 47.0%). This evaluation suggests that using AI as an additional reader can improve the early detection of breast cancer with relevant prognostic features, with minimal to no unnecessary recalls. Although the AI-assisted additional-reader workflow requires additional reads, the higher PPV suggests that it can increase screening effectiveness.
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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.