广西医科大学学报2026，Vol.43Issue(3)：314-325,12.DOI:10.16190/j.cnki.45-1211/r.2026.03.002
大数据驱动的肿瘤病理智能分析:跨越形态学与多组学的诊疗桥梁
Big data-driven intelligent analysis of tumor pathology:a diagnostic and therapeutic bridge across morphology and multi-omics
摘要
Abstract
This paper systematically summarizes the development context,key technologies,and clinical transla-tion applications of big data and artificial intelligence(AI)in intelligent analysis systems for tumor pathology.With the maturation and popularization of whole slide imaging(WSI)technology,tumor pathology analysis is un-dergoing a transformation from traditional digital pathology(DP)to big data-driven AI-based computational pa-thology(CP),providing critical technical support for precision oncology.Technically,this transformation is re-flected in the architectural upgrade from early convolutional neural network(CNN)to vision transformer(ViT)with global receptive field and foundation models(FMs).Meanwhile,weakly supervised learning(WSL)and self-supervised learning(SSL)effectively break through the bottleneck of scarce high-quality annotated data.Clini-cally,AI has been widely applied in globally prevalent cancers such as lung cancer and breast cancer.It not only addresses inter-observer variability through automated grading but also demonstrates considerable potential in identifying subvisual features that are undetectable by human eyes.The introduction of cutting-edge generative AI technologies such as multimodal fusion and virtual staining is further breaking down the barriers between morpho-logy,genomics and transcriptomics,providing more comprehensive decision support for tumor diagno-sis.Although challenges such as domain shift,interpretability,and regulatory and ethical concerns remain to be addressed,establishing a human-machine collaborative intelligent diagnosis and treatment model is becoming a key evolutionary direction for improving diagnostic efficiency and realizing precision medicine,building a core technical bridge for tumor diagnosis and treatment across morphology and multi-omics.关键词
人工智能/临床病理/计算病理学/多组学融合/肿瘤精准诊疗/大数据/虚拟染色/智能诊疗模式Key words
artificial intelligence/clinical pathology/computational pathology/multi-omics fusion/precision tu-mor diagnosis and treatment/big data/virtual staining/intelligent diagnosis and treatment model分类
医药卫生引用本文复制引用
何融泉,李建棣,何世培,张嘉铭,李宗宇,陈国强,唐宇星,陈罡..大数据驱动的肿瘤病理智能分析:跨越形态学与多组学的诊疗桥梁[J].广西医科大学学报,2026,43(3):314-325,12.基金项目
国家自然科学基金资助项目(NSFC82460783) （NSFC82460783）
广西研究生教育创新计划项目(JGY2023068) （JGY2023068）
广西壮族自治区卫生健康委员会科研课题资助项目(Z-A20240554) （Z-A20240554）
