AIMC Topic: Longitudinal Studies
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Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.
Pediatric research
Jan 11, 2024
BACKGROUND: Early identification of children at risk of asthma can have significant clinical implications for effective intervention and treatment. This study aims to disentangle the relative timing and importance of early markers of asthma.
Association between plain water intake and risk of hypertension: longitudinal analyses from the China Health and Nutrition Survey.
Frontiers in public health
Jan 9, 2024
OBJECTIVE: This study aimed to investigate the prospective association between plain water intake and the risk of hypertension based on a longitudinal cohort study in China.
Moderate wine consumption measured using the biomarker urinary tartaric acid concentration decreases inflammatory mediators related to atherosclerosis.
The journal of nutrition, health & aging
Dec 6, 2023
OBJECTIVES: Several studies suggest that moderate wine consumption, particularly red wine, may have benefits for cardiovascular health. Red wine contains a variety of bioactive compounds, including polyphenols like phenolic acids, which have demonstr...
Predicting incident cardiovascular disease among African-American adults: A deep learning approach to evaluate social determinants of health in the Jackson heart study.
PloS one
Nov 10, 2023
The present study sought to leverage machine learning approaches to determine whether social determinants of health improve prediction of incident cardiovascular disease (CVD). Participants in the Jackson Heart study with no history of CVD at baselin...
Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).
Drug and chemical toxicology
Nov 9, 2023
Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utiliz...
Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.
Journal of behavioral addictions
Nov 9, 2023
BACKGROUND AND AIMS: Gaming disorder [GD] risk has been associated with the way gamers bond with their visual representation (i.e., avatar) in the game-world. More specifically, a gamer's relationship with their avatar has been shown to provide relia...
A machine learning approach to identify important variables for distinguishing between fallers and non-fallers in older women.
PloS one
Oct 31, 2023
Falls are a significant ongoing public health concern for older adults. At present, few studies have concurrently explored the influence of multiple measures when seeking to determine which variables are most predictive of fall risks. As such, this c...
Predicting mortality in brain stroke patients using neural networks: outcomes analysis in a longitudinal study.
Scientific reports
Oct 28, 2023
In this study, Neural Networks (NN) modelling has emerged as a promising tool for predicting outcomes in patients with Brain Stroke (BS) by identifying key risk factors. In this longitudinal study, we enrolled 332 patients form Imam hospital in Ardab...
Electroencephalographic abnormalities in children with type 1 diabetes mellitus: a prospective study.
Turkish journal of medical sciences
Oct 12, 2023
BACKGROUND/AIM: The aim herein was to investigate epileptiform discharges on electroencephalogram (EEG), their correlation with glutamic acid decarboxylase 65 autoantibody (GAD-ab) in newly diagnosed pediatric type 1 diabetes mellitus (T1DM) patients...
An improved multiply robust estimator for the average treatment effect.
BMC medical research methodology
Oct 11, 2023
BACKGROUND: In observational studies, double robust or multiply robust (MR) approaches provide more protection from model misspecification than the inverse probability weighting and g-computation for estimating the average treatment effect (ATE). How...
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