Publication Name	World Journal of Radiology
Manuscript ID	108011
Country	China

Category	Radiology, Nuclear Medicine & Medical Imaging
Manuscript Type	Editorial
Article Title	Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy
Manuscript Source	Invited Manuscript
All Author List	Jing-Qi Zeng, Yi-Wei Gao and Xiao-Bin Jia
Funding Agency and Grant Number
Corresponding Author	Jing-Qi Zeng, Academic Fellow, Postdoc, School of Traditional Chinese Pharmacy, China Pharmaceutical University, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, PR China. Electronic address: zjingqi@163.com, Nanjing 211198, Jiangsu Province, China. zjingqi@163.com
Key Words	Low-dose radiation; Immune response; Heterogeneity; Artificial intelligence; Precision medicine; Immunotherapy; Radiomics
Core Tip	Artificial intelligence (AI) is revolutionizing low-dose radiation (LDR) therapy by addressing immune response heterogeneity in patients with cancer. By integrating multidimensional datasets such as immunomics, radiomics, and clinical profiles, AI employs advanced machine learning to decode complex immune patterns and predict individualized therapeutic outcomes. This enables tailored treatment strategies that enhance antitumor efficacy while minimizing side effects. Thus, AI paves the way for precision oncology and by enabling customized treatments for each patient’s unique biological signature.
Citation	Zeng J, Gao Y, Jia X. Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy. World J Radiol 2025; In press

Received	2025-04-03 03:24
Peer-Review Started	2025-04-03 03:24
To Make the First Decision
Return for Revision	2025-04-11 09:55
Revised	2025-04-12 02:56
Second Decision	2025-05-08 02:48
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-05-08 08:41
Articles in Press	2025-05-08 08:41
Publication Fee Transferred
Edit the Manuscript by Language Editor	2025-05-13 20:28
Typeset the Manuscript

ISSN	1949-8470 (online)
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