Objective: The aim of the study is to identify the prospects and possibilities of using artificial intelligence (AI) and domestic software in the provision of organization dental care in the Russian Federation.
Materials And Methods: An analysis of the actual situation on the use of domestic computer programs using AI for the provision of medical care in the Russian Federation was carried out based on information presented on the official websites of software developers, in scientific sources of information and analytical systems of the Higher Attestation Commission, eLibrary, PubMed, Scopus, Google Scholar. Content analysis and analytical method were used, followed by interpretation of the data and conclusions obtained.
Results: To date, information technologies and domestic software aimed at automation, improving safety and quality of medical care are being actively introduced. The requirements for AI-based programs are justified, namely: safety, accessibility for medical professionals and patients, as well as high competitiveness among developers. AI helps to process large amounts of medical data, contributes to the creation of a personalized approach to patient treatment, automates and optimizes administrative processes in healthcare, increases the accuracy of diagnosis, identification of early signs of the disease, predicts the outcome of treatment, neural networks accelerate the development of remote healthcare and telemedicine. However, it is the doctor who should be responsible for the decisions made based on the "tips" and recommendations of artificial intelligence.
Conclusion: The use of computer programs using artificial intelligence in dentistry opens up significant prospects for improving the quality of medical care, interaction with patients and improving the level of education of doctors. The most popular programs will be in therapeutic and pediatric dentistry, aimed, among other things, at the prevention of dental diseases.
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http://dx.doi.org/10.17116/stomat202410305142 | DOI Listing |
Adv Sci (Weinh)
January 2025
College of Physics Science & Technology, School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei University, Baoding, 071002, China.
Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph-structured data. However, most amorphous/polycrystalline oxides-based memristors commonly have unstable conductance regulation due to random growth of conductive filaments. And graph neural networks based on robust and epitaxial film memristors can especially improve energy efficiency due to their high endurance and ultra-low power consumption.
View Article and Find Full Text PDFIntern Emerg Med
January 2025
Emergency Department, National Institute of Medical Sciences and Nutrition Salvador Zubiran, Avenida Vasco de Quiróga No. 15, Colonia Belisario Domínguez Sección XVI, Alcaldía Tlalpan, CP 14080, Mexico City, Mexico.
The COVID-19 pandemic provided an ideal scenario for studying the care of the elderly population, we implemented a tool named the Geriatric Measure (GM) tool to determine the severity and need for hospitalization. The objective of the study is to evaluate if the results of a brief Geriatric Measure tool are associated with mortality and other outcomes among older adults with COVID-19 treated in the emergency department. Retrospective observational cohort study.
View Article and Find Full Text PDFSci Rep
January 2025
Crop and Horticultural Science Research Department, Mazandaran Agricultural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tajrish, Iran.
Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yield prediction, quality control, and market pricing. Traditional methods for estimating fruit weight are often destructive, time-consuming, and labor-intensive. In this study, we addressed the problem of predicting plum FW using artificial intelligence (AI) methods based on fruit dimensions.
View Article and Find Full Text PDFApoptosis
January 2025
Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Cancer-associated fibroblasts (CAFs) significantly influence tumor progression and therapeutic resistance in colorectal cancer (CRC). However, the distributions and functions of CAF subpopulations vary across the four consensus molecular subtypes (CMSs) of CRC. This study performed single-cell RNA and bulk RNA sequencing and revealed that myofibroblast-like CAFs (myCAFs), tumor-like CAFs (tCAFs), inflammatory CAFs (iCAFs), CXCL14CAFs, and MTCAFs are notably enriched in CMS4 compared with other CMSs of CRC.
View Article and Find Full Text PDFSci Rep
January 2025
College of Computer and Information Engineering, Nanjing Tech University, Nanjing, 211800, China.
Graph data is essential for modeling complex relationships among entities. Graph Neural Networks (GNNs) have demonstrated effectiveness in processing low-order undirected graph data; however, in complex directed graphs, relationships between nodes extend beyond first-order connections and encompass higher-order relationships. Additionally, the asymmetry introduced by edge directionality further complicates node interactions, presenting greater challenges for extracting node information.
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