AIMC Topic: Cross-Sectional Studies

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Rate of brain aging associates with future executive function in Asian children and older adults.

eLife
Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health outcomes like cognition. However, there remains a lack of studies investigating the rate of brain aging and its relationship to cognition. Furthermore...

The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting.

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
Many ways of classifying steatotic liver disease (SLD) with metabolic conditions have been proposed. Thus, SLD-related variables were verified using a decision tree. We tested if the suggested components of the actual classification (metabolic dysfun...

Shall we call for a doctor? How to build trust toward AI in healthcare: Insights from a Polish cross-sectional preference study.

Health policy (Amsterdam, Netherlands)
OBJECTIVES: This research aimed to investigate key success factors for the adoption of AI-driven health technologies, particularly in healthcare ecosystems of low digital literacy, such as Poland.

Patient perspectives on AI in radiology: Insights from the United Arab Emirates.

Clinical imaging
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) enhances diagnostic accuracy, efficiency, and patient outcomes in radiology. Patient acceptance is essential for successful integration. This study examines patient perspectives on AI in radiolog...

Current utilization and impact of AI LVO detection tools in acute stroke triage: a multicenter survey analysis.

Neurological research
BACKGROUND: Artificial intelligence (AI) tools for large vessel occlusion (LVO) detection are increasingly used in acute stroke triage to expedite diagnosis and intervention. However, variability in access and workflow integration limits their potent...

Contribution of Labrum and Cartilage to Joint Surface in Different Hip Deformities: An Automatic Deep Learning-Based 3-Dimensional Magnetic Resonance Imaging Analysis.

The American journal of sports medicine
BACKGROUND: Multiple 2-dimensional magnetic resonance imaging (MRI) studies have indicated that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for ...

How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.

BMC psychology
INTRODUCTION: Artificial Intelligence (AI) has become part of our everyday lives and is also increasingly applied in psychosocial healthcare as it can enhance it, make it more accessible, and reduce barriers for help seeking. User behaviour and readi...

Pharmacy students' perceptions of artificial intelligence integration in pharmacy practice: Ethical challenges in multiple countries of the MENA region.

Currents in pharmacy teaching & learning
BACKGROUND: The integration of artificial intelligence (AI) into pharmacy practice has the potential to advance learning experiences and prepare future pharmacists for evolving healthcare needs. However, it also raises ethical considerations that nee...

Pelvic inflammatory disease prevalence and dietary phosphorus: A cross-sectional analysis of the National Health and Nutrition Examination Survey, 2015-2018.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: Emerging evidence suggests dietary components may modulate inflammatory conditions, yet the role of phosphorus in pelvic inflammatory disease (PID) remains unclear. This study investigated the association between dietary phosphorus intake ...

Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.

Journal of clinical periodontology
AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant diseases.