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Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.
Ann Intern Med
January 2025
Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).
Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.
View Article and Find Full Text PDFExploring the Feasibility of a 5-Week mHealth Intervention to Enhance Physical Activity and an Active, Healthy Lifestyle in Community-Dwelling Older Adults: Mixed Methods Study.
JMIR Aging
January 2025
Centre of Expertise in Care Innovation, Department of PXL - Healthcare, PXL University of Applied Sciences and Arts, Hasselt, Belgium.
Background: Advancements in mobile technology have paved the way for innovative interventions aimed at promoting physical activity (PA).
Objective: The main objective of this feasibility study was to assess the feasibility, usability, and acceptability of the More In Action (MIA) app, designed to promote PA among older adults. MIA offers 7 features: personalized tips, PA literacy, guided peer workouts, a community calendar, a personal activity diary, a progression monitor, and a chatbot.
New evidence for early Indian Ocean trade routes into the South African interior.
Proc Natl Acad Sci U S A
February 2025
Cultural Heritage Unit, Conservation Services Division, South African National Parks, Pretoria 0002, South Africa.
The rise and spread of ancient Indian Ocean Rim (IOR) trade networks profoundly impacted southern Africa. Control over this trade played a critical role in the rise and maintenance of complex societies of the second millennium CE such as Mapungubwe and Great Zimbabwe. While the African origins of this trade lie in the first millennium CE, understanding its earliest phases and subsequent development in the far south has been hampered by a general paucity of research.
View Article and Find Full Text PDFAlzheimer's disease image classification based on enhanced residual attention network.
PLoS One
January 2025
School of Emergency Management, Institute of Disaster Prevention, Sanhe, Hebei, China.
With the increasing number of patients with Alzheimer's Disease (AD), the demand for early diagnosis and intervention is becoming increasingly urgent. The traditional detection methods for Alzheimer's disease mainly rely on clinical symptoms, biomarkers, and imaging examinations. However, these methods have limitations in the early detection of Alzheimer's disease, such as strong subjectivity in diagnostic criteria, high detection costs, and high misdiagnosis rates.
View Article and Find Full Text PDFIntelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.
PLoS One
January 2025
School of Information and Communication Engineering, Beijing University of Information Science and Technology, Bei Jing City, China.
To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristor Neural Network (MNN) and an improved Temporal Convolutional Neural Network (TCNN) in network security management. This system not only focuses on the precise classification of vulnerability data but also emphasizes its core role in strengthening the network security management framework. Firstly, the study designs and implements a neural network model based on memristors.
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