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Assessing Nurses' Knowledge Regarding the Application of Artificial Intelligence Among Nursing Practice.
Nurs Res Pract
January 2025
Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Unlabelled: Artificial intelligence (AI) is constantly improving the quality of medical procedures. Despite the application of AI in the healthcare industry, there are conflicting opinions among professionals, and limited research on its practical application in Saudi Arabia was conducted.
Aim: To assess the nurses' knowledge regarding the application of AI in practice at one of the Ministry of Health hospitals in Saudi Arabia.
A novel machine learning based framework for developing composite digital biomarkers of disease progression.
Front Digit Health
January 2025
Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, United States.
Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.
View Article and Find Full Text PDFSalt use patterns and heavy metal urinary excretion.
Front Nutr
January 2025
Clinical Center of Reproductive Medicine, Lianyungang Maternal and Child Health Hospital, Lianyungang, China.
Background: Salt usage patterns have been associated with a risk of multiple diseases; however, their relationship with heavy metal exposure has not been extensively studied.
Methods: This study analyzed survey data from 11,574 NHANES participants. Weighted linear regression models were used to examine the relationship between the type of salt used by participants, the frequency of adding salt at the table, and the frequency of adding regular or seasoned salt to cooking or food preparation, and urinary concentrations of 10 heavy metals.
Background: Lipid Accumulation Product (LAP), which is derived from measurements of waist circumference and triglyceride (TG) levels, serves as a comprehensive indicator of lipid accumulation. Emerging research indicates that lipid accumulation dysfunction might significantly contribute to the pathogenesis of Chronic Obstructive Pulmonary Disease (COPD). Nevertheless, the investigation into the association between LAP and COPD risk is still insufficient, particularly in population-based research.
View Article and Find Full Text PDFPurpose: To develop an algorithm using routine clinical laboratory measurements to identify people at risk for systematic underestimation of glycated hemoglobin (HbA1c) due to p.Val68Met glucose-6-phosphate dehydrogenase (G6PD) deficiency.
Methods: We analyzed 122,307 participants of self-identified Black race across four large cohorts with blood glucose, HbA1c, and red cell distribution width measurements from a single blood draw.
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