Meta-Radiology - KeAi Publishing Communications Ltd | 2024 Cite Score: 10.2 | Q1

Meta-Radiology - KeAi Publishing Communications Ltd | 2024 Cite Score: 10.2 | Q1

• About this Journal:
• Meta-Radiology is a peer-reviewed, open-access interdisciplinary journal focusing on the intersection of radiology, artificial intelligence, data science, and emerging medical technologies.Meta-Radiology is an interdisciplinary journal that provides a forum for the dissemination of new research results in the field of radiology. The typical medical images of interest include those acquired from: magnetic resonance, ultrasound, computed tomography, nuclear medicine, and X-ray.
• The journal aims to advance research on AI-driven diagnostic tools, imaging analytics, computational modeling, and innovations that transform clinical radiology workflows.The types of papers of interest include those that use different modality medical images to perform the following types of clinical and basic science investigations: Clinical radiology : detection, diagnosis, efficacy prediction, prognosis prediction, etc. Artificial intelligence in radiology : segmentation, visualization, feature extraction, image generation, computer-aided diagnosis, computer-aided detection, NLP in radiology, etc.
• It publishes original research articles, reviews, systematic evaluations, technical notes, and perspectives addressing the future of radiology as influenced by digital and computational advancements.
• Published by Elsevier, the journal encourages contributions from radiologists, computer scientists, biomedical engineers, clinicians, imaging specialists, and medical AI researchers.
• The journal emphasizes transparency, reproducibility, and responsible deployment of AI in medical imaging.

• Journal Home:  Journal Homepage

• Editor-in-Chief:  Zhihong Li

• Scope of the Journal:
• Artificial intelligence, machine learning, and deep learning applications in medical imaging.
• Radiomics, image segmentation, feature extraction, and predictive modeling in radiology.
• Clinical decision support systems and AI-based imaging diagnostics.
• Emerging modalities, image reconstruction techniques, and computational imaging innovations.
• Quality assurance, validation, benchmarking, and reproducibility of radiology AI models.
• Ethics, bias, transparency, and regulatory considerations for AI in radiology.
• Imaging workflows, automation, teleradiology, and system-level innovations in radiological practice.
• Interdisciplinary research bridging radiology, computer vision, biomedical engineering, and healthcare data science.
• Latest Research Topics for PhD in Artificial Intelligence
• Latest Research Topics for PhD in Computer Science

• Print ISSN:  29501628

  Electronic ISSN:  

• Abstracting and Indexing:  Scopus

• Imapct Factor :  

• Subject Area and Category:  Computer Graphics and Computer-Aided Design, Radiological and Ultrasound Technology

• Publication Frequency:  

• H Index:  7

• Best Quartile:

  Q1:  Computer Graphics and Computer-Aided Design

  Q2:  

  Q3:  

  Q4:  

• Cite Score:  10.2

• SNIP:  8.294

• Journal Rank(SJR):  2.347

• Latest Articles:   Latest Articles in Meta-Radiology - KeAi Publishing Communications Ltd | 2024 Cite Score: 10.2 | Q1

• Guidelines for Authors: Meta-Radiology - KeAi Publishing Communications Ltd | 2024 Cite Score: 10.2 | Q1 Author Guidelines

• Paper Submissions: Paper Submissions in Meta-Radiology - KeAi Publishing Communications Ltd | 2024 Cite Score: 10.2 | Q1

• Publisher:  KeAi Publishing Communications Ltd.

  Country:  China

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