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| http://dx.doi.org/10.1016/j.aprim.2013.01.007 | DOI Listing |
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[Effect of ICT Use on Glycemic Control in Individuals with Type 2 Diabetes: A Systematic Review].
Rev Med Chil
July 2024
Facultad de Enfermería, Universidad Autónoma de Nuevo León, México.
Unlabelled: Information and communication technologies constitute a resource that can improve the effectiveness of programs focused on people with chronic diseases, especially those with type 2 diabetes mellitus, strengthening the care management provided by the nursing professional.
Aim: To evaluate the available evidence to understand the effects of information and communication technologies on glycaemic control in people with type 2 diabetes.
Material And Methods: Databases used for research were Web of Science, PubMed, and Scopus between January and March of 2023.
Addressing Challenges of Implementing Community First Responder Models based on National and International Experiences: A Systematic Scoping Review.
Iran J Public Health
December 2024
Health in Emergency and Disaster Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
Background: This systematic scoping review aimed to investigate and delineate the dimensions of the Community First Responder (CFR) model implemented in emergency medical services (EMS) across different countries. The primary focus was on identifying key components and characteristics associated with CFR programs.
Methods: This study conducted an extensive search across multiple databases (PubMed, Scopus, and Web of Science) and grey literature sources (Google Scholar, official sites) until Mar 2023 using keywords related to community first responders.
High-intensity versus low-level laser therapy in treatment of patients with subacromial impingement syndrome: a randomized, double-blind, controlled trial.
Lasers Med Sci
January 2025
Basic Science Department, Faculty of Physical Therapy, Cairo University, Cairo, Egypt.
To compare the effects of High-Intensity Laser Therapy (HILT) versus Low-Level Laser Therapy (LLLT) on shoulder pain and disability, shoulder Range of Motion (ROM), Pain Pressure Threshold (PPT), and sleep quality of patients having Subacromial Impingement Syndrome (SAIS). Forty-two patients with SAIS were randomly assigned into three groups, the HILT group (n = 14), the LLLT group (n = 14), and control group (n = 14). All groups received an exercise program consisted of shoulder muscles stretching and strengthening exercises.
View Article and Find Full Text PDFEarly circulating biomarkers to predict plasma leakage in dengue fever.
J Infect
January 2025
School of Biomedical Sciences, Faculty of Medicine, UNSW Sydney, NSW, 2052, Australia; Viral Immunology Systems Program, Kirby Institute, UNSW Sydney, NSW, 2052, Australia. Electronic address:
Background: Dengue, a mosquito-borne viral infection, poses a rapidly growing burden, particularly in low- and middle-income countries. Without early identification of patients at risk of severe outcomes (dengue haemorrhagic fever, severe dengue, and plasma leakage- the latter typically occurring on days 5-7 of illness), untriaged admissions lead to hospital overcrowding and suboptimal care.
Methods: This nested case-control study compared early-stage plasma samples (within the first 96hours of fever) from dengue patients with and without plasma leakage.
Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.
Accid Anal Prev
January 2025
School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK.
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technologies face significant challenges in handling spatiotemporal data and multi-feature fusion, including difficulties in big data processing, and have room for improvement in these areas. To address these issues, this paper proposes a novel method that combines autoencoders, Mahalanobis distance, and dynamic Bayesian networks for anomaly detection.
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