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Results for “искусственный интеллект” — 27 articles
Development of a machine learning model for predicting scleroplasty outcomes in childrenDOI: 10.29188/2712-9217-2025-11-4-38-44, pp. 38-44Introduction. Progressive myopia (nearsightedness) in children represents one of the most acute medical and social problems in modern ophthalmology. Purpose. To develop a machine learning model for predicting the outcome of scleroplasty in children 12 months after surgery. Material and methods. A…
Legal Sovereignty of the Individual in Digital Healthcare in the Era of Artificial IntelligenceDOI: 10.29188/2712-9217-2025-11-4-7-18This analytical study addresses one of the most complex issues in modern law and bioethics: the ownership of medical data in the era of digital healthcare and artificial intelligence. The author conducts a comparative analysis of legal regulations and enforcement practices across three…
The use of AI tools to improve the quality of scientific publications through automated analysis of article preprintsDOI: 10.29188/2712-9217-2025-11-3-32-37, pp. 32-37Introduction. Amid the exponential growth of medical knowledge and publication activity, the speed of disseminating scientific results to the professional community is becoming a critical factor. An assessment of the duration of the peer-review and publication process in biomedical journals…
Digital Health: Forecast for 2025-2030DOI: 10.29188/2712-9217-2025-11-3-7-18, pp. 7-18This report presents a forecast for the development of digital healthcare for the period 2025–2030, based exclusively on the principles of evidence-based medicine (EBM) and an analysis of regulatory trends. The years 2025–2030 will mark a fundamental transition – from the stage of proving concepts…
Intelligent physician decision support system for diagnosis of skin neoplasms based on mobile dermoscopyDOI: 10.29188/2712-9217-2025-11-3-38-44, pp. 38-44Introduction. Malignant skin neoplasms are one of the most pressing problems in modern healthcare, characterized by a steady increase in morbidity. Early diagnosis of initial forms of melanoma by primary care physicians who lack dermoscopy skills presents a particular challenge. The aim of the…
Development of an automated system for bone age assessment in children based on hand radiography using artificial intelligence technologiesDOI: 10.29188/2712-9217-2025-11-3-25-31, pp. 25-31Background. Bone age (BA) assessment is a fundamental tool in pediatrics, pediatric endocrinology, and orthopedics for diagnosing growth and developmental disorders. Traditional manual assessment methods (the Greulich-Pyle atlas, Tanner-Whitehouse method) are characterized by high subjectivity, low…
Intelligent сhatbot MS-Assist for clinical decision support in multiple sclerosisDOI: 10.29188/2712-9217-2025-11-2-19-23, pp. 19-23Multiple sclerosis (MS) represents a significant interdisciplinary challenge requiring accurate and timely diagnosis, as well as complex, long-term patient management. Amid shortages of specialized physicians and high disease variability, digital clinical decision support systems (CDSS) are…
«CORINTEL.TECH»: artificial intelligence for electrocardiogram annotationDOI: 10.29188/2712-9217-2025-11-2-14-18, pp. 14-18The «CORINTEL.TECH» project represents an artificial intelligence (AI)–based software solution for the analysis and annotation of 12-lead electrocardiograms (ECGs). The primary objective of the project is to enhance diagnostic speed and accuracy, optimize healthcare resource utilization, and…
Digital technologies for health promotion and disease prevention in older adultsDOI: 10.29188/2712-9217-2025-11-1-7-22, pp. 7-22Introduction. Population aging poses new challenges to healthcare systems. Older adults often live with multiple chronic conditions, limited mobility, and a need for continuous monitoring. Digital technologies offer innovative approaches to promoting health and preventing disease exacerbations in…
DocAI – An intelligent cross-platform system for optimizing the educational process in medical universitiesDOI: 10.29188/2712-9217-2025-11-1-23-27, pp. 23-27Introduction. Technological progress and recent advances in artificial intelligence (AI) have led to the emergence of solutions aligned with key trends in global education – enhanced flexibility, adaptivity, and personalization of the learning process. One of the major challenges of medical…
Formation of a dataset for a neural network model for recognizing ophthalmological pathology in fundus imagesDOI: 10.29188/2712-9217-2024-10-4-38-42, pp. 38-42Introduction. In ophthalmological practice, the use of digital diagnostic devices has allowed us to accumulate a large database of medical images, and machine learning algorithms make it possible to use this data to create automated solutions that increase the speed, efficiency and quality of…
Prospects for the application of artificial intelligence technologies for the digital transformation of HealthcareDOI: 10.29188/2712-9217-2024-10-3-70-76, pp. 70-76Introduction. Currently, the digital transformation of healthcare is one of the priority areas of industry development. In Russia, there is a high readiness and interest of both managers and doctors in the practical application of various digital products, including decision support systems using…
ChatGPT in medicine: opportunities and limitationsDOI: 10.29188/2712-9217-2024-10-1-33-43, pp. 33-43Introduction. ChatGPT and similar large language model (LLM)/artificial intelligence (AI)-based technologies have been actively implemented in medicine worldwide over the past few years. Materials and Methods. The author analysed the available literature on the application of large language models…
Artificial intelligence in Russian healthcare: collecting and preparing data for machine learningDOI: 10.29188/2712-9217-2023-9-4-7-13, pp. 7-13This scientific article draws attention to the importance of collecting and preparing high-quality medical data for the development of artificial intelligence (AI) systems in Russian healthcare. Materials and methods. The main emphasis is on the need to create a unified federal standard for…
Application of digital technologies in neurologyDOI: 10.29188/2712-9217-2023-9-4-14-22, pp. 14-22Digital technology is the fastest growing area with major implications for healthcare. In neurology, this can provide better accessibility in consultations, expanding the potential of various diagnostic and therapeutic tools and systems. For example, telemedicine allows expanding access to…
Three absolute barriers of digital technologies implementation in medicineDOI: 10.29188/2712-9217-2023-9-2-40-55, pp. 40-55Technologies that are used in medicine cannot be applied in practice in isolation from the basic issues that underlie the health system. In this article the author describes three basic, fundamental barriers to the development of digital technologies in medicine and their implementation in clinical…
Digital transformation of ultrasound diagnosticsDOI: 10.29188/2712-9217-2022-8-4-21-45, pp. 21-45Introduction. Ultrasound (US) is one of the most applied diagnostic methods in the medicine due to its accessibility and non-invasiveness. Twice more ultrasound examinations are conducted in Russia then in economically developed countries. It is necessary to increase the efficiency of ultrasound…
Digital transformation of the pathological service as a way to improve the quality of medical careDOI: 10.29188/2712-9217-2022-8-1-16-40, pp. 16-40Introduction. Pathology plays an essential and important role in diagnostic and choosing patients’ management strategies. The aim of our analytical article is to review opportunities of digital technologies applying to pathology with a focus on converges with clinical disciplines. Materials…
Artificial intelligence in the diagnosis and treatment of kidney stone diseaseDOI: 10.29188/2712-9217-2022-8-1-42-57, pp. 42-57Complex health-care data will be growing exponentially as we enter the era of “big data”. Interpretation and analysis of a large amount of medical data for rapid and personalized decision-making require artificial intelligence-driven technologies and data mining techniques. Over the…
Rating of artificial intelligence startups: prospects for healthcare in RussiaDOI: 10.29188/2712-9217-2021-7-3-32-41, pp. 32-41Summary: Nowadays the work of the healthcare system tends to be based on the care about patient and one of the main goals is to reduce the cost of the service price. One of the steps to reach this goal is to adapt the work of the entire system to the current realities. In all market segments any…