Background: In recent years, Artificial Intelligence (AI) has shown transformative potential in advancing breast cancer care globally. This scoping review seeks to provide a comprehensive overview of AI applications in breast cancer care, examining how they could reshape diagnosis, treatment, and management on a worldwide scale and discussing both the benefits and challenges associated with their adoption. Methods: In accordance with PRISMA-ScR and ensuing guidelines on scoping reviews, PubMed, Web of Science, Cochrane Library, and Embase were systematically searched from inception to end of May 2024. Keywords included “Artificial Intelligence” and “Breast Cancer”. Original studies were included based on their focus on AI applications in breast cancer care and narrative synthesis was employed for data extraction and interpretation, with the findings organized into coherent themes. Results: Finally, 84 articles were included. The majority were conducted in developed countries (n= 54). The majority of publications were in the last 10 years (n= 83). The six main themes for AI applications were AI for breast cancer screening (n= 32), AI for image detection of nodal status (n= 7), AI-assisted histopathology (n= 8), AI in assessing post-neoadjuvant chemotherapy (NACT) response (n= 23), AI in breast cancer margin assessment (n= 5), and AI as a clinical decision support tool (n= 9). AI has been used as clinical decision support tools to augment treatment decisions for breast cancer and in multidisciplinary tumor board settings. Overall, AI applications demonstrated improved accuracy and efficiency; however, most articles did not report patient-centric clinical outcomes. Conclusions: AI applications in breast cancer care show promise in enhancing diagnostic accuracy and treatment planning. However, persistent challenges in AI adoption, such as data quality, algorithm transparency, and resource disparities, must be addressed to advance the field.
背景：近年来，人工智能在全球乳腺癌诊疗领域展现出变革性潜力。本范围综述旨在全面概述人工智能在乳腺癌诊疗中的应用，探讨其如何重塑全球范围内的诊断、治疗与管理模式，并分析应用过程中面临的机遇与挑战。方法：遵循PRISMA-ScR范围综述报告规范，系统检索PubMed、Web of Science、Cochrane Library和Embase数据库自建库至2024年5月末的文献。检索关键词包括"人工智能"与"乳腺癌"。纳入标准为聚焦人工智能在乳腺癌诊疗中应用的原研文献，采用叙述性综合法进行数据提取与解读，并将研究结果归纳为系统性主题。结果：最终纳入84篇文献，其中54项研究来自发达国家，83篇发表于近十年内。人工智能应用主要呈现六大主题：乳腺癌筛查（32篇）、淋巴结状态影像检测（7篇）、辅助组织病理学诊断（8篇）、新辅助化疗疗效评估（23篇）、切缘状态评估（5篇）以及临床决策支持工具（9篇）。人工智能已作为临床决策支持工具应用于乳腺癌治疗方案优化及多学科肿瘤委员会诊疗场景。总体而言，人工智能应用展现出提升诊疗准确性与效率的潜力，但多数研究未报告以患者为中心的临床结局指标。结论：人工智能在乳腺癌诊疗中具有提升诊断精度与治疗规划的潜力，但需解决数据质量、算法透明度及资源不均等持续存在的应用挑战，以推动该领域发展。
肿瘤(癌症)患者之家