Тег - искусственный интеллект
Legal Sovereignty of the Individual in Digital Healthcare in the Era of Artificial Intelligence
DOI: 10.29188/2712-9217-2025-11-4-7-18
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Development of a machine learning model for predicting scleroplasty outcomes in children
DOI: 10.29188/2712-9217-2025-11-4-38-44, page 38-44
Intelligent physician decision support system for diagnosis of skin neoplasms based on mobile dermoscopy
DOI: 10.29188/2712-9217-2025-11-3-38-44, page 38-44
The use of AI tools to improve the quality of scientific publications through automated analysis of article preprints
DOI: 10.29188/2712-9217-2025-11-3-32-37, page 32-37
Development of an automated system for bone age assessment in children based on hand radiography using artificial intelligence technologies
DOI: 10.29188/2712-9217-2025-11-3-25-31, page 25-31
Digital Health: Forecast for 2025-2030
DOI: 10.29188/2712-9217-2025-11-3-7-18, page 7-18
Intelligent сhatbot MS-Assist for clinical decision support in multiple sclerosis
DOI: 10.29188/2712-9217-2025-11-2-19-23, page 19-23
«CORINTEL.TECH»: artificial intelligence for electrocardiogram annotation
DOI: 10.29188/2712-9217-2025-11-2-14-18, page 14-18
DocAI – An intelligent cross-platform system for optimizing the educational process in medical universities
DOI: 10.29188/2712-9217-2025-11-1-23-27, page 23-27
Digital technologies for health promotion and disease prevention in older adults
DOI: 10.29188/2712-9217-2025-11-1-7-22, page 7-22
Formation of a dataset for a neural network model for recognizing ophthalmological pathology in fundus images
DOI: 10.29188/2712-9217-2024-10-4-38-42, page 38-42
Prospects for the application of artificial intelligence technologies for the digital transformation of Healthcare
DOI: 10.29188/2712-9217-2024-10-3-70-76, page 70-76
ChatGPT in medicine: opportunities and limitations
DOI: 10.29188/2712-9217-2024-10-1-33-43, page 33-43
Application of digital technologies in neurology
DOI: 10.29188/2712-9217-2023-9-4-14-22, page 14-22
Artificial intelligence in Russian healthcare: collecting and preparing data for machine learning
DOI: 10.29188/2712-9217-2023-9-4-7-13, page 7-13
Three absolute barriers of digital technologies implementation in medicine
DOI: 10.29188/2712-9217-2023-9-2-40-55, page 40-55
Digital transformation of ultrasound diagnostics
DOI: 10.29188/2712-9217-2022-8-4-21-45, page 21-45
Artificial intelligence in the diagnosis and treatment of kidney stone disease
DOI: 10.29188/2712-9217-2022-8-1-42-57, page 42-57
Digital transformation of the pathological service as a way to improve the quality of medical care
DOI: 10.29188/2712-9217-2022-8-1-16-40, page 16-40
Weaknesses of artificial intelligence in medicine
DOI: 10.29188/2712-9217-2021-7-2-50-52, page 50-52
Legal framework for artificial intelligence technologies in telemedicine
DOI: 10.29188/2712-9217-2021-7-2-18-22, page 18-22
The use of artificial intelligence in predicting patient satisfaction with medical care in a specialized rehabilitation clinic
DOI: 10.29188/2542-2413-2020-6-3-15-23, page 15-23
Deep machine learning (artificial intelligence) in ultrasound diagnostics
DOI: 10.29188/2542-2413-2020-6-2-22-29, page 22-29
Artificial intelligence in medical imaging. Main objectives and development scenarios
DOI: 10.29188/2542-2413-2018-4-3-98-102
The role of artificial intelligence in telemedicine of Russia
DOI: 10.29188/2542-2413-2019-5-1-38-40
