AIMC Topic: Aging

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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...

Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.

Aging
Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse da...

The million-molecule challenge: a moonshot project to rapidly advance longevity intervention discovery.

GeroScience
Targeting aging is the future of twenty-first century preventative medicine. Small molecule interventions that promote healthy longevity are known, but few are well-developed and discovery of novel, robust interventions has stagnated. To accelerate l...

Optimising the care for older persons with complex chronic conditions in home care and nursing homes: design and protocol of I-CARE4OLD, an observational study using real-world data.

BMJ open
INTRODUCTION: In ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home...

Acceptance of social assistant robots for the older adults living in the community in China.

Geriatric nursing (New York, N.Y.)
BACKGROUND: Social assistant robots (SARs) are an important part of providing high quality health and social care for older people, and are an effective measure to promote the development of smart aging. Therefore, it is important to understand the f...

Development of a model for the prediction of biological age.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Rates of aging vary markedly among individuals, and biological age serves as a more reliable predictor of current health status than does chronological age. As such, the ability to predict biological age can support appropri...