摘要
人工智能(AI)在乳腺肿瘤病理诊断中的应用正迅速发展,并逐步向临床实践转化。依托深度学习与数字病理平台,AI辅助诊断技术已在病变区域自动识别、生物标志物定量分析及组织学分级等方面展现出突出优势。同时,AI与分子诊断技术的结合,使基因突变谱与组织学特征的关联分析成为可能,进一步推动了精准医学的落实。随着多模态数据融合能力的提升,通过整合影像学、临床资料、组织病理学及分子生物学等多层次信息,AI有望在乳腺病理诊断中实现更高水平的智能化与个体化。然而,其临床应用仍面临诸多挑战,包括AI技术与临床需求之间的差距、法规与伦理风险,以及重构病理工作流程的阻力等。
The application of artificial intelligence(AI)in the pathological diagnosis of breast tumors is rapidly advancing and gradually transitioning into clinical practice.Leveraging deep learning and digital pathology platforms,AI models have demonstrated remarkable advantages in tasks such as automated lesion detection,quantitative biomarker analysis,and histological grading.Moreover,the integration of AI with molecular diagnostic technologies has enabled the exploration of correlations between genomic mutation profiles and histopathological features,thereby further promoting the implementation of precision medicine.With the enhancement of multimodal data integration,incorporating imaging,clinical records,histopathology,and molecular biology,AI is expected to achieve a higher level of intelligence and individualization in breast pathology diagnosis.However,its clinical application still faces multiple challenges,including discrepancies between AI technologies and clinical needs,regulatory and ethical risks,and resistance associated with restructuring pathological workflows.
作者
刘月平
李健斌
江泽飞
LIU Yueping;LI Jianbin;JIANG Zefei(Department of Pathology,the Fourth Hospital of Hebei Medical University,Tumor Hospital of Hebei Province,Shijiazhuang 050011,China;Department of Oncology,the Fifth Medical Center of Chinese PLA General Hospital,Beijing 100071,China)
出处
《中国肿瘤外科杂志》
2026年第1期6-13,共8页
Chinese Journal of Surgical Oncology
基金
河北省自然科学基金H2024206504。
关键词
乳腺肿瘤
人工智能
大模型
Breast tumor
Artificial Intelligence
Large model
