AIMC Topic: Longitudinal Studies
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A heterogeneity analysis of health-related quality of life in early adults born very preterm or very low birthweight across the sociodemographic spectrum.
Social science & medicine (1982)
Sep 1, 2025
Preterm birth and very low birthweight (VP/VLBW) are associated with poorer health-related quality of life (HRQoL) outcomes extending into adulthood, yet it remains unclear how these effects differ across sociodemographic subgroups. This study aimed ...
Machine learning diagnosis of cognitive impairment and dementia in harmonized older adult cohorts.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Aug 1, 2025
INTRODUCTION: Clinical diagnosis (normal cognition, mild cognitive impairment [MCI], dementia) is critical for understanding cognitive impairment and dementia but can be resource intensive and subject to inconsistencies due to complex clinical judgme...
Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.
Ecotoxicology and environmental safety
Aug 1, 2025
BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence indicates that the key biological processes of oxidative stress, inflammation, and endothelial dysfunct...
Blood immuno-metabolic biomarker signatures of depression and affective symptoms in young adults.
Brain, behavior, and immunity
Aug 1, 2025
BACKGROUND: Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to specific markers, and whether there are subtypes of depression and depressive symptoms which are ass...
Prediction of first attempt of suicide in early adolescence using machine learning.
Journal of affective disorders
Aug 1, 2025
BACKGROUND: Suicide is the second leading cause of death among early adolescents, yet the first onset of suicide attempts during this critical developmental period remains poorly understood. This study aimed to identify key characteristics associated...
Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.
NeuroImage
Jul 15, 2025
Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) te...
Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.
Journal of affective disorders
Jul 15, 2025
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...
Predicting cognitive function among Chinese community-dwelling older adults: A supervised machine learning approach.
Preventive medicine
Jul 1, 2025
OBJECTIVE: Identifying cognitive impairment early enough could support timely intervention of cognitive impairment and facilitate successful cognitive aging. We aimed to build more precise prediction models for cognitive function using less variable ...
Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma.
European journal of radiology
Jul 1, 2025
OBJECTIVES: Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis.
Interpretable machine learning models to predict decline in intrinsic capacity among older adults in China: a prospective cohort study.
Maturitas
Jul 1, 2025
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available for predicting decline in intrinsic capacity among older adults. This study aimed to develop and va...
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