《Radiology-artificial Intelligence》期刊

杂志介绍

JCR分区

中科院分区

1区

影响因子

20.1

CiteScore

21.1

期刊收录

SCIE

Radiology-artificial Intelligence（中文译名：《放射科-人工智能》），ISSN：2638-6100，是Radiological Society of North America Inc.出版的国际性学术期刊，2026年总发文量约64篇。该刊采用非OA开放访问，学科归属为Multiple。该刊是医学、计算机人工智能领域的国际权威刊物，已被SCIE（科学引文索引扩展版）等国际主流学术数据库收录。2026年期刊影响因子达20.1，2025年期刊CiteScore为21.1，2025年期刊自引率约2%，在中科院期刊分区体系中位列医学大类1区TOP 期刊，在所属学科领域具备高学术影响力与国际认可度。Radiology-artificial Intelligence长期聚焦医学、计算机人工智能及相关产业的技术应用前沿，在稿件录用评判中，该刊将创新性与前沿性作为核心遴选标准，重点收录能够对医学、计算机人工智能领域的落地与发展产生实质性推动价值的研究成果。

期刊评价

名词解释：

影响因子（Impact Factor, IF）：指该期刊前两年发表的文章，在第三年的平均被引用次数。它反映了期刊的近期平均影响力和热度。

中科院分区：中科院分区表是国内主流的学术期刊分级评价工具，核心意义是建立跨学科可比的统一评价标尺，为职称评审、学位授予、科研立项等科研管理工作提供标准化量化依据，同时帮助科研人员筛选优质期刊、规避学术风险，适配国内本土化的科研评价需求。

期刊分区表

《新锐期刊分区表》（2026年3月发布）

大类学科	小类学科	Top期刊	综述期刊
医学 1区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核医学 1区 1区	是	否

期刊分区表（2025年3月升级版）

大类学科	小类学科	Top期刊	综述期刊
医学 1区	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机：人工智能 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核医学 1区 2区	是	否

JCR分区

2025-2026年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q1	5 / 210	97.9
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	SCIE	Q1	1 / 217	99.8
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	SCIE	Q1	7 / 210	96.9
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	SCIE	Q1	3 / 217	98.85

2023-2024年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	ESCI	Q1	21 / 197	89.6
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q1	9 / 204	95.8
学科：COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	ESCI	Q1	20 / 198	90.15
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q1	12 / 204	94.36

中国学者近期发文

Quantifying the Privacy-Utility Trade-off in Medical Imaging A

Author:Yu, Zekai

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 2, pp. -. DOI: 10.1148/ryai.251044

Quantifying the Privacy-Utility Trade-off in Medical Imaging AI The Respons

Author:Yu, Zekai

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 2, pp. -. DOI:

Adnexal Lesion Discrimination Using Deep Learning Analysis of Dynamic Contrast-enhanced US Image

Author:Wu, Manli; Yang, Hong; Chen, Ying; Wu, Shuangyu; Liang, Tianming; Zhang, Man; Qu, Enze; Sun, Xiaofeng; Zhang, Rui; Mu, Liang; Xiao, Li; Wen, Hong; Wang, Ruili; Liu, Tingting; Meng, Xiaotao; Su, Manting; Wang, Ying; Gu, Jian; Chen, Sijia; Wang, Yaping; Zhao, Qinghong; Liu, Juan; Cheng, Ping; Wang, Ruixuan; Hu, Jianfang; Zhang, Xinling

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 1, pp. -. DOI: 10.1148/ryai.240786

Deep Learning for Coronary Stenosis Detection in Heavily Calcified Plaques at Coronary CT Angiography: A Stepwise, Multicenter Stud

Author:Wang, Rui; Wang, Siwen; Zhang, Libo; Schoepf, U. Joseph; Zhang, Fandong; Chen, Wei; Zhou, Zhen; Fang, Zhe; Hu, Bin; Yu, Yizhou; Zhang, Jiayin; Wang, Ximing; Zhang, Longjiang; Xu, Lei

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 1, pp. -. DOI: 10.1148/ryai.250109

Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Modelwith Multiview Mammograms and Associated Report

Author:Gao, Yuan; Zhou, Hong-Yu; Wang, Xin; Portaluri, Antonio; Zhang, Tianyu; Beets-Tan, Regina; Han, Luyi; Lu, Chunyao; Estacio, Laura; Da'ngelo, Anna; Ursprung, Stephan; Yu, Yizhou; Teuwen, Jonas; Tan, Tao; Mann, Ritse

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 1, pp. -. DOI: 10.1148/ryai.240646

Gastric Neoplasm Detection at Contrast-enhanced CT with Deep Learnin

Author:Chen, Xin; Xia, Yingda; Yao, Lisha; Li, Suyun; Liang, Yanting; Zheng, Zhilin; Yuan, Mingze; Yao, Jiawen; Zhang, Ruiping; Tu, Wenting; Guo, Yongmei; Liang, Dan; Ma, Zelan; Chen, Dandan; Lai, Lisha; Xie, Xiaowen; Yu, Yifan; Jia, Yanlian; Zhang, Ling; Liu, Zaiyi

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2026; Vol. 8, Issue 1, pp. -. DOI: 10.1148/ryai.250145

Pseudo-Contrast-enhanced US via Enhanced Generative Adversarial Networks for Evaluating Tumor Ablation Efficac

Author:Chen, Chen; Yu, Jiabin; Xu, Zhikang; Xu, Changsong; Zhou, Zubang; Hao, Jindong; Wang, Vicky Yang; Yao, Jincao; Zhou, Lingyan; Xu, Chenke; Song, Mei; Zhang, Qi; Liu, Xiaofang; Sui, Lin; Yan, Yuqi; Jiang, Tian; Zhou, Yahan; Wu, Yingtianqi; Xiao, Binggang; Xu, Chenjie; Mi, Hongmei; Yang, Li; Wu, Zhiwei; He, Qingquan; Chen, Jian; Liu, Qi; Xu, Don

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2025; Vol. 7, Issue 3, pp. -. DOI: 10.1148/ryai.240370

Evaluating Performance of a Deep Learning Multilabel Segmentation Model to Quantify Acute and Chronic Brain Lesions at MRI after Stroke and Predict Prognosi

Author:Tang, Tianyu; Cui, Ying; Lu, Chunqiang; Li, Huiming; Zhou, Jiaying; Zhang, Xiaoyu; Zhou, Yujie; Zhang, Ying; Zhang, Yi; Xu, Yuhao; Li, Yuefeng; Ju, Shenghong

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2025; Vol. 7, Issue 3, pp. -. DOI: 10.1148/ryai.240072

Incremental Prognostic Value of Pericoronary Adipose Tissue Attenuation at Coronary CT Angiography for Prediction of Major Adverse Cardiovascular Events in Individuals with Diabetes Mellitu

Author:Ding, Yipu; Shan, Dongkai; Han, Tianwen; Liu, Zinuan; Wang, Xi; Dou, Guanhua; Xin, Ran; Guo, Ziqiang; Chen, Guanxi; Jing, Jing; He, Bai; Chen, Yundai; Yang, Junjie

Journal: RADIOLOGY-ARTIFICIAL INTELLIGENCE. 2025; Vol. 7, Issue 2, pp. -. DOI: 10.1148/ryct.240242