Practice and prospects of artificial intelligence in breast tumor pathology diagnosis
LIU Yueping
LI Jianbin
JIANG Zefei
Abstract：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.
Keywords：Breast tumorArtificial IntelligenceLarge model
Publication Date：2026-02-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：8( 6-13 )