AIMC Topic: Cross-Sectional Studies

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Deep learning application for the classification of Alzheimer's disease using F-flortaucipir (AV-1451) tau positron emission tomography.

Scientific reports
The positron emission tomography (PET) with F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of F-flort...

Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study.

Journal of nursing management
BACKGROUND: Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms amon...

An AI model to estimate visual acuity based solely on cross-sectional OCT imaging of various diseases.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop an artificial intelligence (AI) model for estimating best-corrected visual acuity (BCVA) using horizontal and vertical optical coherence tomography (OCT) scans of various retinal diseases and examine factors associated with its ac...

Deep Learning-Based Estimation of Implantable Collamer Lens Vault Using Optical Coherence Tomography.

American journal of ophthalmology
PURPOSE: To develop and validate a deep learning neural network for automated measurement of implantable collamer lens (ICL) vault using anterior segment optical coherence tomography (AS-OCT).

EE-Explorer: A Multimodal Artificial Intelligence System for Eye Emergency Triage and Primary Diagnosis.

American journal of ophthalmology
PURPOSE: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images.

Differential diagnosis of secondary hypertension based on deep learning.

Artificial intelligence in medicine
Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology identification can eliminate aetiologies and control blood pressure. However, inexperienced doctors o...

Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia.

Medicina (Kaunas, Lithuania)
: The role of the pharmacist in healthcare society is unique, since they are providers of health information and medication counseling to patients. Hence, this study aimed to evaluate Awareness, Perceptions, and Opinions towards Artificial intelligen...

A Risk Prediction Model for Physical Restraints Among Older Chinese Adults in Long-term Care Facilities: Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Numerous studies have identified risk factors for physical restraint (PR) use in older adults in long-term care facilities. Nevertheless, there is a lack of predictive tools to identify high-risk individuals.

Associations Between Older Adults' Loneliness and Acceptance of Socially Assistive Robots: A Cross-Sectional Study.

Journal of gerontological nursing
The use of socially assistive robots (SARs) to enable older adults (aged ≥65 years) to live independently for as long as possible has been researched for several years. Of particular interest is the way SARs can combat loneliness. A quantitative cros...

Leptin levels in childhood tuberculosis and its correlation with body mass index, IFN-γ, and TNF-α in an Indonesian population.

The Indian journal of tuberculosis
BACKGROUND: Leptin plays a key role in the regulation of energy and inflammation in tuberculosis (TB). However, its correlation in children with TB remains unclear. Therefore, this study aimed to evaluate the correlations between body mass index, IFN...