Moscow introduces AI Radiology Training Manuals to enhance medical imaging education

RUSSIA—The Center for Diagnostics and Telemedicine of the Moscow Healthcare Department has released two new educational manuals designed to help healthcare professionals develop practical skills in the use of artificial intelligence (AI) in radiology.

The publications aim to support the growing integration of AI into medical imaging and to strengthen clinicians’ ability to use these technologies safely and effectively in everyday practice.

New Resources for AI-Powered Radiology

The first manual, Application of Medical Devices Based on Artificial Intelligence Technologies in Radiology: Brain Computed Tomography, Chest Computed Tomography and X-ray, Mammography, provides comprehensive guidance on the use of AI-enabled tools across several key imaging modalities.

The second publication, Simulator of a Radiologist’s Workstation with AI-Powered Services, provides a practical learning environment in which users can interact with AI applications in a simulated clinical setting.

The manuals target a broad audience, including medical students, radiology residents, practicing radiologists, healthcare managers, and medical informatics specialists.

Through practical exercises, case studies, and self-assessment quizzes, learners can gain hands-on experience in image interpretation, AI-assisted reporting, and integrating computer vision technologies into radiology workflows.

According to Yuri Vasilev, Medical Director of the Center for Diagnostics and Telemedicine and Chief Officer of Radiology at the Moscow Health Care Department, AI has become an essential tool in modern radiology.

He noted that clinicians must not only understand the principles behind AI technologies but also learn how to apply them correctly in clinical practice.

The manuals allow users to explore neural network outputs in a controlled educational environment while building competencies that support faster and more accurate diagnostic decision-making.

Built on real-world experience

The educational materials draw heavily on Moscow’s large-scale experiment with computer vision technologies in medical image analysis.

Researchers combined findings from clinical trials, real-world deployments, and ongoing evaluations of AI-powered medical devices to create practical learning resources.

The manuals explain the principles behind AI applications in radiology and provide recommendations for analyzing brain and chest CT scans, X-rays, and mammograms.

They also highlight both successful and incorrect algorithm outputs, helping users understand the strengths and limitations of AI systems and learn to assess their diagnostic accuracy and clinical effectiveness.

Anton Vladzimirsky, Deputy Director for Research at the Center, said the publications reflect years of experience gained from deploying AI technologies in routine clinical practice.

Rather than focusing solely on technical capabilities, the manuals present real-world use cases, challenges, and limitations that clinicians may encounter when using AI-assisted tools.

Supporting Moscow’s expanding AI ecosystem

The release comes as Moscow continues to expand its AI-driven healthcare infrastructure.

Artificial intelligence is now fully integrated into the city’s radiology services, where more than 60 computer vision tools support clinicians across dozens of clinical specialties.

These systems have already analyzed more than 30 million imaging studies and assist in detecting conditions such as lung cancer, stroke, coronary artery disease, osteoporosis, pneumonia, and aortic aneurysms.

Recent developments have further strengthened Moscow’s AI ecosystem.

Earlier this year, the Center reported a 23% reduction in radiology reporting times following the introduction of structured AI-supported reporting templates.

The initiative is helping radiologists manage increasing workloads while maintaining diagnostic quality.

In addition, Moscow continues to expand the national MosMedAI platform, which now connects more than 2,000 healthcare organizations across 74 Russian regions and provides access to AI-powered imaging services that have undergone rigorous clinical evaluation.

Recognition and educational adoption

Both manuals have received recommendations from the Coordinating Council for Education in the Field of Healthcare and Medical Sciences for use in educational institutions.

The Radiologist Workstation Simulator with Artificial Intelligence-Powered Services has been approved for residency training programs in radiology, and the Application of Medical Devices Based on AI technologies in radiology, the manual has also been endorsed for educational use in the healthcare sciences.

Established in 1996, the Center for Diagnostics and Telemedicine remains one of Russia’s leading institutions for medical AI research, radiology innovation, healthcare digitalization, and professional training.

Alongside advances in radiology, the Center has supported the deployment of AI-powered clinical decision support systems and electronic health record summarization tools that help physicians streamline patient care and improve workflow efficiency.