One of the new developments in the field of artificial intelligence (AI) is the Chat-GPT (Generative Pre-trained Transformer) technology, a capacious linguistic model based on the analysis of big data using powerful computing systems through the aggregation of certain algorithms. Such technologies are capable of “understanding” and composing texts close to those created by humans. Their improvement and implementation can lead to better quality and accessibility of medical care for patients, including patients with diabetes mellitus (DM).
The aim of this work was to summarize all available and relevant information about the applicability of Chat-GPT technology in patients with DM.
Materials and methods. The search for relevant information sources was carried out through Pubmed / Medline database. “ChatGPT diabetes” was used as search combination.
Results. Chat-GPT is a fairly new AI technology (start of use - November 2022), and there is a limited amount of published data available regarding its implementation in treatment of patients with DM. This review systematizes and generalizes approaches to assessing the prospects for Chat-GPT application as well as summarizes some its characteristics. Rare research results show that Chat-GPT has the ability to provide valuable information about diabetes in many cases. However, it is necessary to approach the use of this technology with great caution since the system does not always generate completely correct, accurate and detailed answers. A mechanism for assessing the quality of responses from such systems should be developed.
Conclusion. This study is limited to information available in open sources. It is rational to continue studies of Chat-GPT accuracy and precision. It is obvious that improving the system by training on large amounts of medical data updated in real time might open up new prospects for its application.

Experts predict global health spending to reach $16.9 trillion by 2050. However, 20% to 40% of all resources invested could be lost due to various forms of project inefficiency. An analysis of the content of three key information resources offering methodological and instrumental support for research aimed at the assessment of the cost-effectiveness of projects implemented in national health care systems was carried out. The resources analyzed were the following: World Health Organization's Choosing Interventions that are Cost-Effective (WHO CHOICE), Guide to economic analysis and research (GEAR) and Disease control priorities (DCP).
Each of the information resources provides unique, non-duplicate content that provides decisions making support based on data from assessment of the cost-effectiveness of projects and activities in the healthcare system. WHO-CHOICE uses a “generalized” approach to cost-effectiveness analysis, a standardized methodology that helps measuring the impact of health interventions and identifying priorities for further development. An interactive tool OneHealth, developed based on WHO-CHOICE, provides the ability to simulate a wide range of scenarios, strategies and their combinations. GEAR provides methodological support for cost-effectiveness assessment algorithms, including smart maps for decision-making, a database of practical guidelines and the opportunity to get an expert advice. The DCP provides access to an organized online collection of publications and generates a periodic review of the most relevant evidence on cost-effective interventions to address the burden of disease in the setting of scarce resources
It is concluded that the reviewed information resources effectively summarize international practices in analyzing the costeffectiveness of healthcare projects while still having a number of limitations for use in domestic research. The need to create our own accessible and regularly updated interactive tools for the economic assessment of medical interventions is substantiated, taking into account the national and regional characteristics of the functioning of the Russian Federation healthcare system.

This paper analyzes Russian-language Android applications for psychological help, defines requirements and recommendations for the development of such apps. Psychological applications have been selected from the Google Play Market according to certain criteria. Therapeutic and engagement functions, goals, tags, number of downloads, and average score of each application have been recorded for the analysis. The aesthetics and usability of each application have also been evaluated on a five-point scale by 7 user-respondents.
We found a variety of functional content in the applications. According to the respondents, most of the applications had an attractive and user-friendly design.
However, only one study examined the experience of using one of these applications that indicates the topic is insufficiently studied in Russia. It is also emphasized that the adaptation of questionnaire using the MARS method can help evaluating the effectiveness of an application at the development stage.
Research and analysis of mobile applications for psychological well-being can be useful for developers and specialists in the psychology to build more effective and user-friendly applications.

Aim: to study digital health technologies presented in dissertation research in the specialty “Public Health and Healthcare” for 2018-2022.
Materials and methods: We found 194 dissertations posted on the official website of the Higher Attestation Commission in the specialty “Public Health and Healthcare” (02/14/03) for 2018-2022. We identified 72 dissertations which studied the use of digital technologies in healthcare.
The analysis of the obtained data was carried out using the interactive computing environment Jupiter Notebook and the software libraries Pandas (1.5.3), scikit-learn, Matplotlib and Seaborn for processing, analyzing (frequency) data, creating a structured dataset, constructing a trend line and graphical Images.
Results: During 2018-2022, 37.1% of dissertations defended in this specialty used digital technologies, and were aimed at the development, use of information and analytical systems and the creation of electronic registers. The number of scientific works in this area is decreasing, although they are of interest not only to health care organizers, but also to doctors. Scientific research was most active in the Central and Volga Federal Districts, covering all types of digital technologies, which defines these districts as drivers in the development of digital health care and singles them out for targeted investment.

The role of digital technologies in medicine is getting bigger each year. However, digital skills of healthcare professionals remain a primary limiting factor in the adoption of more advanced technological solutions. This research presents survey data conducted on the Continuous Medical and Pharmaceutical Education portal, involving over 18 000 healthcare professionals. Groups were identified and analyzed based on their level of digital competencies. We found that in healthcare institutions where conditions for the development of digital competencies among medical professionals exist, the level of these competencies is higher, as reflected in their proficiency with medical information systems and the utilization of telemedicine technologies

Background. Primary hyperparathyroidism (PHPT) is an endocrine disease characterized by excessive production of parathyroid hormone (PTH) and elevated or high-normal blood calcium levels caused by primary pathology of the parathyroid glands. The "classic" complication of PHPT is a decrease in the kidneys filtration function. Parathyroidectomy (PTE) reduces the risks of further deterioration in filtration function; however, in some cases, this is not achieved.
Aim. To develop a mathematical model to predict the decline in estimated glomerular filtration rate (eGFR) 12 months after PTE in patients with PHPT, and implement it as a software.
Methods. Retrospective study included 140 patients with PHPT who underwent PTE in 1993–2010 and 2018–2020 at the National Medical Research Center of Endocrinology. Analyzed variables included sex, age, indicators of calciumphosphorus, purine, lipid, and carbohydrate metabolism, presence of PHPT complications, treatment for PHPT, histological examination of removed parathyroid tissue, development of postoperative hypocalcemia and transient hypoparathyroidism, therapy for postoperative hypocalcemia. The random forest method was used to build the mathematical model.
Results. To predict the decline in eGFR, a model using 24 predictors was built: sex, age, body mass index, PTH, ionized calcium, alkaline phosphatase, phosphorus, urea, eGFR, total cholesterol, diastolic blood pressure, SD(T-score)<-2.5/ SD(Z-score)<-2.0, CKD, duration of nephrolithiasis, use of angiotensin II receptor blockers and angiotensin-converting enzyme inhibitors, preoperative use of cholecalciferol and cinacalcet, parathyroid hyperplasia/adenoma, postoperative hypocalcemia, dose of alfacalcidol and calcium supplements, postoperative use of cholecalciferol. The resulting model (http://194.87.111.169/cfr) predicts a decline in eGFR in patients with PHPT after PTE with a probability of 56.8–86.3% and excludes – with a probability of 85.6–97.7%.
Conclusion. A mathematical model to predict the decline in eGFR 12 months after PTE in patients with PHPT was developed, with an overall accuracy of 88%, 95% CI (79%; 93%). The model was implemented as a calculator that can be used in routine clinical practice

The study attempted to test experts' assumptions about the difference in the genetic mechanisms of the formation of emotional and volitional deficits in schizophrenia with predominance of negative disorders. The aim of the study is to create empirical theory of these two phenomena using an approach based on JSM-method for automated research support (JSM-method ARS). Polymorphisms of four genes associated with schizophrenia (BDNF, 5HTR2A, HTTLPR, ZNF804A) and clinical data presented as PANSS score were used as empirical data.
The use of generalized JSM-method ARS, which generates ternary relationships “cause-blocker-effect”, allows us considering in detail the interaction of specific gene variants for emotional and volitional deficits in negative schizophrenia.
The result of the study is confirmation of the experts' hypothesis about the difference in the mechanisms of these clinical manifestations. This conclusion was based on a comparison of knowledge fragments for two phenomena.
The utilized approach can be extrapolated to a larger number of genes. We suggest that the use of the generalized JSM-method ARS is a promising approach to studying gene interactions in schizophrenia