Translated with AI
The future of medicine and new opportunities for using artificial intelligence in tuberculosis treatment were among the key topics of the meeting of the CIS Working Group on Tuberculosis, which took place on June 4 in Moscow, the press service of the CIS Executive Committee reported.
The expert meeting took place on the sidelines of the 2nd International Congress of Respiratory Health Specialists, "Respiratory Medicine in the CIS Countries: Focus on Socially Significant Infections." The event was initiated by the National Medical Research Center for Phthisiopulmonology and Infectious Diseases of Russia, with the support of the Russian Ministry of Health and the CIS Executive Committee.
Representatives from Azerbaijan, Armenia, Belarus, Kazakhstan, Kyrgyzstan, Russia, Tajikistan, Turkmenistan, and Uzbekistan participated in the meeting. Representatives from the World Health Organization Regional Office for Europe, the Regional Delegation of the International Committee of the Red Cross to the Russian Federation and the Republic of Belarus, and the CIS Executive Committee also joined the discussion.
Participants focused on the implementation of modern digital technologies and artificial intelligence systems in TB practice. The discussion focused on sharing experiences, demonstrating technological advances, and finding solutions to current challenges in the fight against tuberculosis.
As noted during the meeting, the TB services of the Commonwealth countries are undergoing a period of profound technological modernization. Countries in the region are demonstrating some of the fastest rates of decline in tuberculosis incidence and mortality in the world. However, the spread of drug-resistant forms of the disease and the need to accelerate the eradication of the infection require new approaches. One such solution is the transition from traditional monitoring to digital epidemiological management.
In the CIS countries, pilot projects to integrate neural network technologies into primary healthcare continue to be implemented and expanded. Automated X-ray screening (CAD-CXR), which enables screening in hard-to-reach and sparsely populated areas, has become widely used. Using computer vision technologies, these systems analyze fluorographic and X-ray images, identifying signs of tuberculosis in the early, preclinical stages. One important task remains training artificial intelligence to detect not only tuberculosis but also other lung diseases.
The experts paid special attention to the problem of multidrug-resistant tuberculosis, which remains one of the main challenges facing modern phthisiology in the Commonwealth countries. To address this issue, they proposed increasing the use of predictive analytics and big data technologies.
According to experts, the integration of machine learning methods enables a comprehensive analysis of electronic medical records, pathogen genotyping results, and patient molecular genetic biomarkers. Based on this data, artificial intelligence systems can assist in the selection of individualized anti-tuberculosis treatment regimens, proactively assess the risk of toxic complications, and predict treatment effectiveness before it begins.
Furthermore, mobile IT platforms for video-monitored therapy using AI-based biometric identification technologies are already being used in the CIS countries. These solutions enable remote, personalized monitoring of patient compliance and ensure continuity of treatment during outpatient treatment.
Further digitalization of tuberculosis care is reflected in the draft Joint Action Plan of the CIS Member States to Prevent the Spread of Tuberculosis for 2027–2030. The document was submitted to the CIS Economic Commission in June of this year and provides for the further integration of digital tools and intelligent systems into disease control practices.
The experts also noted that cross-border exchange of depersonalized data and the unification of digital standards are key factors in achieving the global goals of the World Health Organization's End TB Strategy. They believe that the creation of interoperable AI systems for screening and patient care will enable the scaling of successful practices and accelerate the digital transformation of national healthcare systems in the Commonwealth of Independent States.
During the meeting, participants considered the Belarusian Ministry of Health's initiative to establish a core organization for CIS member states in the field of phthisiology. The Republican Scientific and Practical Center for Pulmonology and Phthisiology of Belarus was proposed as such an organization.
Additionally, members of the Working Group discussed issues related to medical support for migrant workers. Based on the results of the roundtable discussion "Observation and Monitoring of Migrants' Health: Experiences of Interagency Cooperation," which took place on May 20, 2026, in Minsk, a decision was made to develop recommendations in this area. Experts plan to begin drafting the document in the third quarter of this year.
