AIMC Topic: Longitudinal Studies

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[Cluster predictors of trajectories of leisure-time physical activity intensity in men and women from ELSA-Brasil].

Cadernos de saude publica May 19, 2025
The maintenance of physical activity over time is a challenge for public health. Predictors of different physical activity intensities have not been sufficiently analyzed. This study aimed to identify clusters of trajectories of physical activity int...
Adult Male Middle Aged Brazil Exercise Humans Female Surveys and Questionnaires Leisure Activities Socioeconomic Factors Longitudinal Studies Cluster Analysis Sex Factors
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Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

JMIR aging Apr 30, 2025
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...
Humans China Machine Learning Cognitive Dysfunction Prospective Studies Longitudinal Studies Biomarkers East Asian People Female Longevity Aged Aged, 80 and over Male
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Development of an artificial intelligence model for assisting periodontal therapy decision-making: A retrospective longitudinal cohort study.

Journal of dentistry Apr 24, 2025
OBJECTIVES: This study aims to develop and validate an artificial intelligence (AI) - driven model to assist periodontal therapy decision-making and minimize tooth loss.
Humans Artificial Intelligence Machine Learning Retrospective Studies Clinical Decision-Making Longitudinal Studies Decision Making Periodontal Diseases Alveolar Bone Loss Tooth Loss Female Aged Adult Male Middle Aged
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Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis.

BMC public health Apr 24, 2025
BACKGROUND: Understanding the complex interplay between life course exposures, such as adverse childhood experiences and environmental factors, and disease risk is essential for developing effective public health interventions. Traditional epidemiolo...
Humans Artificial Intelligence Deep Learning Longitudinal Studies
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Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

NPJ primary care respiratory medicine Apr 23, 2025
Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-ma...
Adult Asthma Male Middle Aged Humans Machine Learning Female Risk Factors Aged Risk Assessment Primary Health Care Logistic Models Longitudinal Studies Scotland
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Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction.

Scientific reports Apr 22, 2025
Biological age (BA) and frailty represent two distinct health measures that offer valuable insights into the aging process. Comparing and analyzing blood-based biomarkers from the machine learning (ML) predictors of BA and frailty helps deepen our un...
China Longitudinal Studies Frailty Cystatin C Aged Humans Aged, 80 and over Machine Learning Male Biomarkers Aging Female Middle Aged
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Integrating Machine Learning and Follow-Up Variables to Improve Early Detection of Hepatocellular Carcinoma in Tyrosinemia Type 1: A Multicenter Study.

International journal of molecular sciences Apr 18, 2025
Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to...
Tyrosinemias Early Detection of Cancer alpha-Fetoproteins Alkaline Phosphatase Alanine Transaminase Middle Aged Infant Adolescent Child, Preschool Infant, Newborn Child Young Adult Liver Neoplasms Humans Adult Carcinoma, Hepatocellular Machine Learning Biomarkers, Tumor Longitudinal Studies Retrospective Studies Male Follow-Up Studies Female
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Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach.

BMC psychology Apr 17, 2025
BACKGROUND: Aging has become a global trend, and depression, as an accompanying issue, poses a significant threat to the health of middle-aged and older adults. Existing studies primarily rely on statistical methods such as logistic regression for sm...
China Depression Longitudinal Studies Aged, 80 and over Humans Male Machine Learning Aging Female Middle Aged Risk Factors Aged
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Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.

Cardiovascular diabetology Apr 16, 2025
BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD)....
Incidence Time Factors Insulin Resistance Longitudinal Studies Metabolic Syndrome Middle Aged Risk Assessment China Blood Glucose Kidney Diseases Predictive Value of Tests Decision Support Techniques Prospective Studies Biomarkers Humans Prognosis Machine Learning Female Risk Factors Aged Male Cardiovascular Diseases
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Longitudinal brain age in first-episode mania youth treated with lithium or quetiapine.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology Apr 13, 2025
It is unclear if lithium and quetiapine have neuroprotective effects, especially in early stages of bipolar and schizoaffective disorders. Here, an age-related multivariate brain structural measure (i.e., brain-PAD) at baseline and changes in respons...
Psychotic Disorders Quetiapine Fumarate Antipsychotic Agents Mania Young Adult Humans Adult Brain Male Bipolar Disorder Female Adolescent Antimanic Agents Treatment Outcome Longitudinal Studies Magnetic Resonance Imaging
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