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The Future of Breast Cancer Organized Screening Program Through Artificial Intelligence: A Scoping Review
Emma Altobelli1, Paolo Matteo Angeletti1,2, Marco Ciancaglini3
1Department of Life, Health and Environmental Sciences, Section of Epidemiology and Biostatistics Unit, University of L'Aquila, 67100 L'Aquila, Italy.
Artificial intelligence (AI) in breast cancer screening significantly reduces radiologist reading time and improves diagnostic accuracy. AI shows promise in reducing errors and detecting subtle abnormalities, potentially equaling double human reading in opportunistic screening.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Breast cancer screening faces persistent diagnostic challenges.
- Integrating artificial intelligence (AI) into screening workflows is being explored to address these issues.
Purpose of the Study:
- To conduct a scoping review evaluating AI's role in breast cancer screening.
- To assess AI's potential to resolve remaining diagnostic issues in breast cancer detection.
Main Methods:
- Searched PubMed, Web of Science, and Scopus databases up to May 28, 2024.
- Applied PRISMA methodology for article selection.
- Classified studies by type (meta-analysis, trial, prospective, retrospective) and screening context (organized vs. opportunistic).
Main Results:
- AI reduced radiologist reading time by 17-91% and improved diagnostic accuracy.
- AI software potentially reduces false negatives/positives and detects subtle abnormalities.
- AI in organized screening improved recall rate, specificity, and PPV; in opportunistic screening, it reduced interval cancers.
Conclusions:
- AI is a promising technology with significant healthcare system impact.
- In opportunistic screening with a single human reader, AI can enhance diagnostic performance to match double human reading.
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