AI Medical Compendium Topic

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Longitudinal Studies

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Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate pot...

Predicting Homelessness Among Transitioning U.S. Army Soldiers.

American journal of preventive medicine
INTRODUCTION: This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention.

Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

Magma (New York, N.Y.)
OBJECTIVE: Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. This work aimed to develop and evaluate automated abdominal SAT/VAT segmentation on longitudinal MRI in adults with o...

Early prediction of pediatric asthma in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort using machine learning.

Pediatric research
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
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
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
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
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
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
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...