Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects

Abstract Artificial intelligence (AI) offers transformative potential in pathology, where histopathological images remain the diagnostic gold standard due to their rich morphological and molecular information. While the rapid development of AI-driven computational pathology tools is revolutionizing...

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Bibliografiske detaljer

Principais autores:	Xiu-Ming Zhang, Tian-Hong Gao, Qiu-Yu Cai, Jia-Bin Xia, Yu-Ning Sun, Jian Yang, Wei-Han Li, Sheng-Xu-Ming Zhang, Heng-Rui Lou, Xiao-Tian Yu, Kai-Wen Hu, Jing-Wen Ye, Jin-Xing Zhang, Jie Lei, Le-Chao Cheng, Lin-Jie Xu, Qing Chen, He-Xiang Wang, Mei-Fu Gan, Cheng Lu, Nan Pu, Ming-Li Song, Xin Chen, Wen-Jie Liang, Han Lv, Chao-Qing Xu, Zai-Yi Liu, Jing Zhang, Kai Yan, Zun-Lei Feng
Format:	Artigo
Sprog:	Inglês
Udgivet:	KeAi Communications Co., Ltd. 2026-01-01
Serier:	Military Medical Research
Fag:	Artificial intelligence (AI) Pathology images Quantitative feature Pathology foundation model
Online adgang:	https://doi.org/10.1186/s40779-025-00680-6
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