AIMC Topic: Aging

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Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
As the aging population in the United States grows, the need for an integrated approach to support older adults has become increasingly urgent. The SUNSHINE framework, Seniors Uniting Nationwide to Support Health, INtegrated Care, and Evolution, offe...

Transcriptome analysis and machine learning methods reveal potential mechanisms of zebrafish muscle aging.

Comparative biochemistry and physiology. Part D, Genomics & proteomics
Muscle is one of the most abundant tissues in the human body, and its aging usually leads to many adverse consequences. Zebrafish is a powerful model used to study human muscle diseases, yet we know little about the molecular mechanisms of muscle agi...

How to measure and model cardiovascular aging.

Cardiovascular research
Most acquired cardiovascular diseases are more common in older people, and the biological mechanisms and manifestations of aging provide insight into cardiovascular pathophysiology. Measuring aging within the cardiovascular system may help to better ...

Brain Age Prediction: Deep Models Need a Hand to Generalize.

Human brain mapping
Predicting brain age from T1-weighted MRI is a promising marker for understanding brain aging and its associated conditions. While deep learning models have shown success in reducing the mean absolute error (MAE) of predicted brain age, concerns abou...

CT Biomarkers for Phenotypic Biological Aging: Emerging Concepts and Advantages.

Radiographics : a review publication of the Radiological Society of North America, Inc
Aging is a complex phenomenon reflecting the time-dependent accumulation of damage that results in progressive structural and functional decline, disease risk, and death. Chronological age (CA) is an imperfect measure of health but remains an importa...

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Computers in biology and medicine
Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigate...

In-silico evaluation of aging-related interventions using omics data and predictive modeling.

Ageing research reviews
A major challenge in aging research is identifying interventions that can improve lifespan and health and minimize toxicity. Clinical studies cannot usually consider decades-long follow-up periods, and therefore, in-silico evaluations using omics-bas...

Brain age prediction from MRI scans in neurodegenerative diseases.

Current opinion in neurology
PURPOSE OF REVIEW: This review explores the use of brain age estimation from MRI scans as a biomarker of brain health. With disorders like Alzheimer's and Parkinson's increasing globally, there is an urgent need for early detection tools that can ide...

Role of Brain Age Gap as a Mediator in the Relationship Between Cognitive Impairment Risk Factors and Cognition.

Neurology
BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CeVD) and cognitive impairment risk factors contribute to cognitive decline, but the role of brain age gap (BAG) in mediating this relationship remains unclear, especially in Southeast Asian populat...

Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.

Ageing research reviews
Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent cells promotes chronic inflammation, tissue dysfunction, age-related diseases, and tumor suppression. ...