Moscow Diagnostics and Telemedicine Centre staff win Russia’s Quality Leader 2026 awards
Yuri Vasilev, the Centre’s Medical Director, received the Quality Director 2026 award, while Alexander Borisov, a researcher in its Department of Medical Informatics, Radiomics and Radiogenomics, won the Breakthrough of the Year category.
RUSSIA — Two employees of Moscow’s Center for Diagnostics and Telemedicine have won the Russian Quality Leader 2026 awards for improving diagnostic efficiency and integrating artificial intelligence into medical imaging.
Yuri Vasilev, the Centre’s Medical Director, received the Quality Director 2026 award, while Alexander Borisov, a researcher in its Department of Medical Informatics, Radiomics, and Radiogenomics, won the Breakthrough of the Year category.
AI-driven radiology management improves efficiency
Under Vasilev’s leadership, the Centre developed a diagnostic radiology management model that has reduced the time needed to prepare radiology reports by 88%.
The solution delivers verified annual economic benefits exceeding RUB 301 million (US$3.3 million).
Following a directive from the Russian President, authorities are expanding its implementation nationwide.
Vasilev has also contributed to developing 42 national standards, including six GOST R standards, and holds 172 patents in Russia.
The model uses artificial intelligence to improve the organization of diagnostic services, focusing on reporting speed, diagnostic accuracy and resource utilization.
“For us, the quality of medical care is not an abstract metric, but a measurable outcome reflected in the time required to prepare a report, its quality, the clinical validity of diagnostic decisions and the efficient use of resources,” Vasilev said.
He explained that integrating AI allows healthcare providers to rethink diagnostic workflows rather than simply automate individual tasks. He also noted that the model’s demonstrated performance provides a basis for its expansion across Russia.
Neural networks automate X-ray quality control
The second award recognized Borisov’s development of an ensemble of seven convolutional neural networks designed to automatically assess the quality of X-ray images.
Integrated into Moscow’s Unified Radiological Information Service (URIS), which operates within the Unified Medical Information and Analysis System (UMIAS), the technology evaluates images in 14 seconds, achieving an accuracy rate of more than 95%.
The system identifies poor-quality scans before they affect clinical workflows, helping healthcare facilities reduce repeat examinations and unnecessary radiation exposure.
It also supports more efficient use of resources financed through Russia’s compulsory medical insurance system.
The research formed the basis of Borisov’s PhD thesis.
“Our goal was to make X-ray quality control fast, accurate and suitable for everyday clinical practice. The algorithm assesses an image in 14 seconds, allowing the check to take place within the diagnostic workflow,” Borisov said.
He noted that the technology helps identify imaging problems early, reducing the likelihood of repeat examinations.
Its integration into Moscow’s healthcare infrastructure also demonstrates how research can translate into operational digital health applications.
National recognition for healthcare quality initiatives
The All-Russian Quality Leader competition receives support from federal ministries, government agencies and public organizations.
In 2026, its Expert Council assessed more than 200 applications from over 35 Russian regions.
The Supervisory Board selected 11 winners for their contributions to national quality infrastructure, advanced management systems, digital transformation and organizational efficiency.
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