AI病理文献周选｜第02期（2026.05.24）

每周日更新，速览病理AI新进展，与您不见不散!

本期整理了8篇近期值得关注的病理AI研究，覆盖IHC细胞计数、肝癌血管模式量化、肾脏空间糖组学、肿瘤免疫浸润评估、胃癌淋巴结转移预测、乳腺癌TIL标准化评测、膀胱癌免疫表型判读，以及H&E预测空间转录组等方向。

1. HESpotEx: a dual-stream deep learning framework for spot-level gene expression prediction from histological images, Nature Computational Science

2. Rank-aware agglomeration of foundation models for immunohistochemistry image cell counting, Medical Image Analysis

3. Artificial intelligence-based vascular pattern profiling predicts prognosis and therapeutic response in hepatocellular carcinoma, Journal of Advanced Research

4. Analysis of computational tumor-infiltrating lymphocytes in breast cancer from the results of the TIGER challenge, Nature Communications

5. Deep learning-based prediction of lymph node metastasis and occult tumor cells in gastric cancer using histopathological images: a retrospective study, British Journal of Cancer

6. Development and validation of artificial intelligence-based model for bladder cancer immunophenotyping using whole slide images, npj Precision Oncology

7. AI-Based Digital Pathology-Enabled Spatial-Omics Data Analyses of the Human Kidney, Journal of Proteome Research

8. Estimating tumour immune infiltration: methodological convergence across histology and spatial technologies, Briefings in Bioinformatics

这几篇研究既有面向具体临床问题的AI模型，也有面向空间组学、多模态整合和标准化评测的方法学工作。您最希望我们在“AI病理视界”公众号中精读并解析哪一篇？欢迎在评论区留言告诉我们！