Artificial intelligence‐driven change redefining radiology through interdisciplinary innovation

Artificial intelligence‐driven change redefining radiology through interdisciplinary innovation

Abstract Artificial intelligence (AI) is rapidly advancing, yet its applications in radiology remain relatively nascent. From a spatiotemporal perspective, this review examines the forces driving AI development and its integration with medicine and radiology, with a particular focus on advancements...

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Bibliographic Details
Main Authors:	Runqiu Huang, Xiaolin Meng, Xiaoxuan Zhang, Zhendong Luo, Lu Cao, Qianjin Feng, Guolin Ma, Di Dong, Yang Wang
Format:	Article
Language:	English
Published:	Wiley-VCH 2025-01-01
Series:	Interdisciplinary Medicine
Subjects:	artificial intelligence deep learning interdisciplinary application radiology
Online Access:	https://doi.org/10.1002/INMD.20240063
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