AIMC Topic: Cross-Sectional Studies

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Mental speed is high until age 60 as revealed by analysis of over a million participants.

Nature human behaviour
Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion mo...

Use of a deep learning and random forest approach to track changes in the predictive nature of socioeconomic drivers of under-5 mortality rates in sub-Saharan Africa.

BMJ open
OBJECTIVES: We used machine learning algorithms to track how the ranks of importance and the survival outcome of four socioeconomic determinants (place of residence, mother's level of education, wealth index and sex of the child) of under-5 mortality...

Machine learning-based prediction of critical illness in children visiting the emergency department.

PloS one
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...

Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach.

Frontiers in endocrinology
BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies have evaluated the association between multivitamins intake and obesity in children and adolescents.

Antemortem detection of Parkinson's disease pathology in peripheral biopsies using artificial intelligence.

Acta neuropathologica communications
The diagnosis of Parkinson's disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized th...

Artificial intelligence model to identify elderly patients with locomotive syndrome: A cross-section study.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
BACKGROUND: Identifying elderly individuals with locomotive syndrome is important to prevent disability in this population. Although screening tools for locomotive syndrome are available, these require time commitment and are limited by an individual...

Linking Function and Structure with ReSensNet: Predicting Retinal Sensitivity from OCT using Deep Learning.

Ophthalmology. Retina
PURPOSE: The currently used measures of retinal function are limited by being subjective, nonlocalized, or taxing for patients. To address these limitations, we sought to develop and evaluate a deep learning (DL) method to automatically predict the f...

Reproducibility of deep learning based scleral spur localisation and anterior chamber angle measurements from anterior segment optical coherence tomography images.

The British journal of ophthalmology
AIMS: To apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning loca...

Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program.

Scientific reports
The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial i...

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

Rheumatology international
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitu...