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Association between physical activity levels and stroke risk among Chinese adults aged 45 and over based on CHARLS.
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School of Physical Education, Southwest Petroleum University, Chengdu, 610500, China.
Stroke is one of the leading causes of death in developing countries, and China bears the largest global burden of stroke. This study aims to investigate the relationship between different dimensions of physical activity levels and stroke risk using a nationally representative database. We performed a cross-sectional analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) 2020.
View Article and Find Full Text PDFRobust self management classification via sparse representation based discriminative model for mild cognitive impairment associated with diabetes mellitus.
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December 2024
The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Fuzhou, 350122, Fujian, China.
Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e.
View Article and Find Full Text PDFGlobal changes in extreme tropical cyclone wave heights under projected future climate conditions.
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Weather Program Office, Ocean and Atmospheric Research, NOAA, Silver Spring, MD, USA.
Tropical cyclone risks are expected to increase with climate change. One such risk is extreme ocean waves generated by surface winds from these systems. We use synthetic databases of both historical (1980-2017) and future (2015-2050) tropical cyclone tracks to generate wind fields and force a computationally efficient wave model to estimate significant wave heights across all global tropical cyclone basins.
View Article and Find Full Text PDFDevelopment of a prognostic gene signature and exploration of P4HA1 in the modulation of cuproptosis in colorectal cancer.
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School of Pharmacy, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Cuproptosis, a newly identified form of cell death, has drawn increasing attention for its association with various cancers, though its specific role in colorectal cancer (CRC) remains unclear. In this study, transcriptomic and clinical data from CRC patients available in the TCGA database were analyzed to investigate the impact of cuproptosis. Differentially expressed genes linked to cuproptosis were identified using Weighted Gene Co-Expression Network Analysis (WGCNA).
View Article and Find Full Text PDFWeb application using machine learning to predict cardiovascular disease and hypertension in mine workers.
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Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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