About the Journal

The Journal of Machine Intelligence in Radiology Health (JMIRH) is a premier, peer-reviewed, open-access academic journal dedicated to exploring cutting-edge advancements in artificial intelligence, machine learning, and their transformative applications in radiology and medical imaging. Established to address the rapidly evolving intersection of computational science and diagnostic medicine, JMIRH provides a global platform for researchers, radiologists, engineers, and policymakers to share innovative research and practical insights.

Focus and Scope

JMIRH bridges the gap between theoretical machine intelligence and clinical radiological practice. The journal invites contributions that demonstrate the development, validation, and ethical implementation of AI tools to enhance diagnostic accuracy, workflow efficiency, and patient outcomes in imaging health.

Key Topics Include:

  • Deep learning models for medical image analysis (X-ray, CT, MRI, ultrasound)

  • AI-driven detection, classification, and segmentation of pathologies

  • Radiomics and machine intelligence for predictive biomarker discovery

  • Natural language processing for automated radiology report generation and analysis

  • Integration of AI into clinical radiology workflows and PACS systems

  • Ethical considerations, bias mitigation, and regulatory frameworks for AI in imaging

  • Human-AI collaboration and comparative studies of AI vs. radiologist performance

The journal welcomes a wide range of submissions, including original research articles, technical notes, case studies, review articles, and perspectives on future trends.

Open Access Policy

Committed to the free exchange of knowledge, JMIRH operates under an open-access model, ensuring that all articles are freely available to readers worldwide. This accessibility fosters collaboration across disciplines, supporting a vibrant research community.

Authors retain copyright over their work and license it under the Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing for broad sharing and adaptation with proper attribution.

Copyright Notice

Authors publishing in JMIRH agree to the following:

  • Copyright remains with the authors, while the journal holds the right to first publication.

  • Articles are distributed under the CC BY 4.0 license, enabling unrestricted use and distribution with appropriate credit.

  • Authors are encouraged to share their work on personal or institutional platforms to increase visibility and impact.

Sponsorship and Disclosure

The Journal of Machine Intelligence in Radiology Health thrives on the dedication of its editorial board, reviewers, and contributors. Any external funding or sponsorship will be transparently disclosed to maintain the journal’s integrity and independence.

Archiving and Preservation

JMIRH participates in globally recognized digital preservation programs, including LOCKSS (Lots of Copies Keep Stuff Safe) and CLOCKSS, ensuring perpetual access to all published content even in the face of unforeseen disruptions.

Privacy Statement

At JMIRH, the privacy of authors, reviewers, and readers is paramount. The journal collects personal information solely for operational purposes, such as editorial workflows and communication. This information is never shared with third parties without explicit consent, except as required by law.

Our Vision

The Journal of Machine Intelligence in Radiology Health (JMIRH) was founded with a mission to illuminate the profound impact of artificial intelligence on the future of radiology. By fostering a collaborative and inclusive environment, JMIRH seeks to inspire innovation, shape ethical practices, and contribute to smarter, more accurate, and efficient diagnostic medicine.