AIMC Topic: Age Factors

Clear Filters Showing 11 to 20 of 394 articles

Dynamic Changes in Metabolic Syndrome Scores and New-Onset Stroke Risk in Middle-Aged and Older Adults: A Nationwide Prospective Cohort Study in China Aligned With Predictive, Preventive, and Personalized Medicine.

Journal of the American Heart Association
BACKGROUND: Despite the established link between metabolic syndrome (MetS) and stroke incidence, the effects of dynamic and cumulative MetS scores on stroke risk among middle-aged and older populations in China remain inadequately explored. Furthermo...

Longitudinal development of sex differences in the limbic system is associated with age, puberty and mental health.

Communications biology
Sex differences in mental health become more evident across adolescence, with a two-fold increase of prevalence of mood disorders in females compared to males. The brain underpinnings remain understudied. Here, we investigated the role of age, pubert...

Machine learning models for predicting renal injury in patients with gout.

Renal failure
BACKGROUND: Renal injury is a severe complication among individuals diagnosed with gout. This research constructed a machine learning predictive model to assess renal injury risk in gout patients.

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity.

BMC cardiovascular disorders
BACKGROUND: Obesity is a disease with high heterogeneity. Both overall obesity and central obesity are associated with increased risks of having cardio-metabolic co-morbidities. This study is aimed to examine the cardio-metabolic characteristics and ...

Age-specific prevalence and predictors of lifetime suicide attempts using machine learning in Chinese adults: a nationwide multi-centre survey.

Epidemiology and psychiatric sciences
AIMS: The epidemiology and age-specific patterns of lifetime suicide attempts (LSA) in China remain unclear. We aimed to examine age-specific prevalence and predictors of LSA among Chinese adults using machine learning (ML).

Estimating the peak age of chess players through statistical and machine learning techniques.

Scientific reports
Because chess is played in formal tournaments and competitive environments, it requires physical and mental endurance. This endurance declines as the years progress and can decrease the player's performance. As the player's age increases, elements su...

Age-related variation in hemoglobin glycation index and stroke mortality: mediation and machine learning in a cohort study.

Scientific reports
To investigate the associations between both age and the hemoglobin glycation index (HGI) and the 30-day and 1-year mortality in ischemic stroke (IS) patients and to analyze the mediating effect of the HGI on the relationship between age and mortalit...