Morgan Matthew B, Mates Jonathan L
Department of Radiology and Imaging Sciences, University of Utah, 50 North Medical Drive, Salt Lake City, UT 84132, USA.
Viz.ai, San Francisco, CA, USA.
Radiol Clin North Am. 2021 Jan;59(1):139-148. doi: 10.1016/j.rcl.2020.08.007.
Artificial intelligence (AI) technology shows promise in breast imaging to improve both interpretive and noninterpretive tasks. AI-based screening triage may help identify normal examinations and AI-based computer-aided detection (AI-CAD) may increase cancer detection and reduce false positives. Risk assessment, quality assurance, and other workflow tasks may also be streamlined. AI adoption will depend on robust evidence of improved quality, increased efficiency, and cost-effectiveness. Reliance on AI will likely proceed through stages and will involve careful attention to its limitations to prevent overconfidence in its application.
人工智能（AI）技术在乳腺成像方面展现出改善解读和非解读任务的潜力。基于AI的筛查分诊有助于识别正常检查结果，基于AI的计算机辅助检测（AI-CAD）可能提高癌症检出率并减少假阳性。风险评估、质量保证及其他工作流程任务也可能得到简化。AI的应用将取决于其在提高质量、提升效率和成本效益方面的有力证据。对AI的依赖可能会分阶段进行，并且需要仔细关注其局限性，以防止在应用中过度自信。
