The first neural network designed for the analysis of scientific publications has undergone testing in Moscow. Researchers from the Center for Diagnostics and Telemedicine within the Moscow Department of Health successfully evaluated the capabilities of the "Sechenov DataMed.AI" neural network. Beyond conventional functions such as searching, filtering, and viewing keywords within scientific papers, this  neural network exhibits the capability to identify abstract keywords from search queries within the text, as well as clustering discovered publications by subject. This tool proves particularly advantageous for specialists tasked with swiftly processing substantial data from diverse databases.

Yury Vasiliev, Senior Consultant for Radiology of the Moscow Health Department, CEO of the Center for Diagnostics and Telemedicine, emphasized the demand for effective tools to facilitate rapid information retrieval, given the rapid influx of biomedical information and the escalating number of publications. In September 2023, the scientific staff of the Center received test access to the "Sechenov DataMed.AI" neural network, underscoring its potential to significantly expedite the preparation of systematic reviews, meta-analyses, scientific article sections, keyword selection, and prompt responses to specific scientific inquiries. Vasiliev also highlighted the strategic importance of domestically developing such tools, supporting scientific development.

The neural network is poised to enhance efforts in advancing new scientific directions, analyzing global research experiences, and preparing scientific publications. Experts note that the functionality of this new development rivals that of only a select few foreign online services.

Established in 1996, the Center for Diagnostics and Telemedicine is a preeminent scientific and practical organization within the Moscow Department of Health Care. Specializing in the integration of artificial intelligence technologies in medicine, radiation diagnostics development, organizational aspects of medical departments, scientific research, and medical worker education.

The Center serves as a scientific foundation for the implementation of indigenous innovations in the medical field, primarily focusing on practical applications. Our research efforts result in methodological recommendations for healthcare professionals, simulation models for calibration of medical devices, training materials for medical personnel, programming products, standardization guidelines, and scientific publications.