Academic Journal
Q1Radiology: Artificial Intelligence
About Radiology: Artificial Intelligence
Radiology: Artificial Intelligence is a scholarly journal published by Radiological Society of North America Inc.. SCImago 2025 lists it in Q1, with an SJR of 4.61 and H-index of 56.
Coverage: 2019-2026. Research categories: Artificial Intelligence (Q1); Radiological and Ultrasound Technology (Q1); Radiology, Nuclear Medicine and Imaging (Q1).
Source-backed journal facts
Topics in published research
Radiomics and Machine Learning in Medical Imaging; Artificial Intelligence in Healthcare and Education; AI in cancer detection; COVID-19 diagnosis using AI; Radiology practices and education; Medical Imaging and Analysis.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
Deep Learning Analysis of Dual-Modality US Videos for the Characterization of Superficial Lymphadenopathy
Yangyang Zhu, Ran Cao, Zhibin Zhu, Jinxia Zhang et al.
2026-09-30 · DOI: 10.1148/ryai.260131Checklist for Artificial Intelligence in Medical Imaging (CLAIM): Explanation, Elaboration, and Examples
Tugba Akinci D'Antonoli, Lisa C. Adams, Amine Amyar, Ken Chang et al.
2026-09-30 · DOI: 10.1148/ryai.260835A Deep Learning Model to Predict Breast Cancer Recurrence Using Longitudinal Mammograms and Clinical Data
Chunyao Lu, Xin Wang, Tianyu Zhang, Xinglong Liang et al.
2026-09-09 · DOI: 10.1148/ryai.250941DeepVEST: Deep Learning-based Vessel Segmentation and Erasure in Breast MRI for Improved Lesion Assessment
Marco Cantone, Tianyu Zhang, Claudio Marrocco, Luyi Han et al.
2026-09-09 · DOI: 10.1148/ryai.250630Benchmarking of AI and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation at Screening CT: The LUNA25 Challenge
Dré Peeters, Bogdan Obreja, Noa Antonissen, Zaigham Saghir et al.
2026-09-01 · DOI: 10.1148/ryai.260179Human-AI Collaboration in Radiology: The Blind Spots
Su Hwan Kim, Lisa C. Adams, Benedikt Wiestler, Dennis M. Hedderich et al.
2026-09-01 · DOI: 10.1148/ryai.260325Who’s on First? Prioritizing Radiology Examinations in the Emergency Department
Daniela Pfeiffer, Johannes Benedikt Thalhammer
2026-09-01 · DOI: 10.1148/ryai.260778Predetermined Change Control Plan Adoption and Documentation Transparency in U.S. Food and Drug Administration–cleared Radiology Artificial Intelligence/Machine Learning Devices
Ketan Dayma, Palak Patel, Kenneth Hildreth, Tamara Jamaspishvili et al.
2026-09-01 · DOI: 10.1148/ryai.260385Simulation of AI-driven CT Queue Prioritization in the Emergency Department
Erica Silva, Kevin Tang, Sam Chiacchia, Xiaoman Zhang et al.
2026-09-01 · DOI: 10.1148/ryai.260110Image Quality in the Era of Artificial Intelligence: Understanding the Limitations of AI-based Image Reconstruction and Postprocessing
Jana G. Delfino, Jason L. Granstedt, Frank W. Samuelson, Robert Ochs et al.
2026-09-01 · DOI: 10.1148/ryai.260100Assuring Transparency of AI Software after Deployment
Irvine Sihlahla
2026-09-01 · DOI: 10.1148/ryai.260811What LUNA25 Teaches Us about AI for Lung Cancer Screening
Eduardo Moreno Júdice de Mattos Farina, Gilberto Szarf
2026-09-01 · DOI: 10.1148/ryai.260657A Deep Learning Model Incorporating Spatiotemporal Asymmetries on Longitudinal Mammograms to Predict Breast Cancer Risk
Zhengbo Zhou, Dooman Arefan, Margarita L. Zuley, Jules H. Sumkin et al.
2026-09-01 · DOI: 10.1148/ryai.250888Anatomy-specific Performance of CT Angiography–based AI for Anterior Circulation Occlusion: Systematic Review and Meta-Analysis
Yike Liu, Chaofan Li, Zepeng Ren, Yuchen Hu et al.
2026-07-29 · DOI: 10.1148/ryai.260261Artificial Intelligence as a Triage Partner in Breast Cancer Screening
Michael S. Yao, Allison Chae
2026-07-01 · DOI: 10.1148/ryai.260493AI as a Safety Net Reader for Mammograms Classified as Normal or Benign in the French Screening Program
Christophe Tourasse, Benoît Mesurolle, Maud Ottavy, Patricia Soler-Michel et al.
2026-07-01 · DOI: 10.1148/ryai.250989Automated Delineation of Couinaud Segments at CT for Future Liver Remnant Volumetry
Tejas Sudharshan Mathai, Praveen T. S. Balamuralikrishna, Vivek Batheja, Xinya Wang et al.
2026-07-01 · DOI: 10.1148/ryai.250808Development and Validation of a Deep Learning–enabled Single Breath-hold Abbreviated MRI Protocol for Hepatocellular Carcinoma Diagnosis
Yunfei Zhang, Zhijun Geng, Xianling Qian, Yuyao Xiao et al.
2026-07-01 · DOI: 10.1148/ryai.250914Artificial Intelligence for Digital Breast Tomosynthesis Screening with and without Prior Examinations in BreastScreen Norway
Nataliia Moshina, Marthe Larsen, Åsne S. Holen, Hildegunn S. Aase et al.
2026-07-01 · DOI: 10.1148/ryai.250988Alignment of Policy, Practice, and Patient Safety for Trustworthy AI in Radiology
Florence X. Doo, Melissa A. Davis, Jason Poff, Yvonne W. Lui et al.
2026-07-01 · DOI: 10.1148/ryai.250982Reviews
Community Reviews
Version History
September 11, 2026 at 2:15 am
September 11, 2026