AIMC Topic: Cross-Sectional Studies
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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis.
Scientific reports
Aug 21, 2025
The accurate classification of obesity is essential for public health and clinical decision-making. Traditional anthropometric measures such as body mass index (BMI) have limitations in differentiating between fat and lean mass. This study aimed to e...
The additive effect of the estimated glucose disposal rate and a body shape index on cardiovascular disease: A cross-sectional study.
PloS one
Aug 21, 2025
BACKGROUND: The glucose disposal rate (eGDR) and a body shape index (ABSI) are predictors strongly associated with cardiovascular disease (CVD) and outcomes. However, whether they have additive effects on CVD risk is unknown. This study aimed to inve...
Medication adherence among Jordanian adults with chronic conditions: a combined analysis using regression and machine learning.
Annals of medicine
Aug 20, 2025
BACKGROUND: Managing chronic illness effectively depends not only on treatment availability but also on patients' ability to adhere to prescribed medications.
Cancer care coordination determinants of depression in head and neck cancer survivors.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Aug 20, 2025
PURPOSE: This study aims to explore the role of patient-reported cancer care coordination in explaining depression among head and neck (HNC) cancer survivors.
Factors that influence technophobia in Chinese older patients with ischemic stroke: a cross-sectional survey.
BMC geriatrics
Aug 19, 2025
BACKGROUND: Older patients with ischemic stroke often have a large number of medical needs, technophobia refers to the irrational anxiety and fear of digital technologies such as mobile communication equipment, artificial intelligence and robots, res...
Acceptance of AI-Powered Chatbots Among Physiotherapy Students: International Cross-Sectional Study.
JMIR medical education
Aug 19, 2025
BACKGROUND: Artificial intelligence-powered chatbots (AI-PCs) are increasingly integrated into educational settings, including health care disciplines. Despite their potential to enhance learning, limited research has investigated physiotherapy (PT) ...
The association of symptoms, pulmonary function test and computed tomography in interstitial lung disease at the onset of connective tissue disease: an observational study with artificial intelligence analysis of high-resolution computed tomography.
Rheumatology international
Aug 12, 2025
Interstitial lung disease (ILD) is a common and serious organ manifestation in patients with connective tissue disease (CTD), but it is uncertain whether there is a difference in ILD between symptomatic and asymptomatic patients. Therefore, we conduc...
Attitudes, Perceptions, and Factors Influencing the Adoption of AI in Health Care Among Medical Staff: Nationwide Cross-Sectional Survey Study.
Journal of medical Internet research
Aug 8, 2025
BACKGROUND: Artificial intelligence (AI) has demonstrated transformative potential in the health care field; yet, its clinical adoption faces challenges such as inaccuracy, bias, and data privacy concerns. As the primary operators of AI systems, phys...
Liver MRI proton density fat fraction inference from contrast enhanced CT images using deep learning: A proof-of-concept study.
PloS one
Aug 8, 2025
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease worldwide, affecting over 30% of the global general population. Its progressive nature and association with other chronic diseases make...
Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.
BMC health services research
Aug 7, 2025
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...
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