AIMC Topic: Aging

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ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age.

The lancet. Healthy longevity
BACKGROUND: Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framew...

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Nature communications
Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical ...

Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers.

Sensors (Basel, Switzerland)
Mild cognitive impairment (MCI) is the precursor to the advanced stage of Alzheimer's disease (AD), and it is important to detect the transition to the MCI condition as early as possible. Trends in daily routines/activities provide a measurement of c...

Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Cell
Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integ...

Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms.

BMC medical informatics and decision making
INTRODUCTION: The global society is currently facing a rise in the elderly population. The concept of successful aging (SA) appeared in the gerontological literature to overcome the challenges and problems of population aging. SA is a subjective and ...

Quantification of golgi dispersal and classification using machine learning models.

Micron (Oxford, England : 1993)
The Golgi body is a critical organelle in eukaryotic cells responsible for processing and modifying proteins and lipids. Under certain conditions, such as stress, disease, or ageing, the Golgi structure alters. Therefore, understanding the mechanisms...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

Scientific reports
An increasing and aging patient population poses a growing burden on healthcare professionals. Automation of medical imaging diagnostics holds promise for enhancing patient care and reducing manpower required to accommodate an increasing patient-popu...

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...

Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND While there is a growing body of research examining opinions on social robots in elderly care, there is a lack of comprehensive studies investigating the underlying factors influencing these opinions. The Godspeed Questionnaire Series (GQS...

Chest radiography as a biomarker of ageing: artificial intelligence-based, multi-institutional model development and validation in Japan.

The lancet. Healthy longevity
BACKGROUND: Chest radiographs are widely available and cost-effective; however, their usefulness as a biomarker of ageing using multi-institutional data remains underexplored. The aim of this study was to develop a biomarker of ageing from chest radi...