AIMC Topic: Aging

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Using deep learning to associate human genes with age-related diseases.

Bioinformatics (Oxford, England)
MOTIVATION: One way to identify genes possibly associated with ageing is to build a classification model (from the machine learning field) capable of classifying genes as associated with multiple age-related diseases. To build this model, we use a pr...

Realizing the Potential of Robotics for Aged Care Through Co-Creation.

Journal of Alzheimer's disease : JAD
Socially assistive robots have the potential to improve aged care by providing assistance through social interaction. While some evidence suggests a positive impact of social robots on measures of well-being, the adoption of robotic technology remain...

Classification of Alzheimer's Disease with Respect to Physiological Aging with Innovative EEG Biomarkers in a Machine Learning Implementation.

Journal of Alzheimer's disease : JAD
BACKGROUND: Several studies investigated clinical and instrumental differences to make diagnosis of dementia in general and in Alzheimer's disease (AD) in particular with the aim to classify, at the individual level, AD patients and healthy controls ...

Machine Learning in Aging Research.

The journals of gerontology. Series A, Biological sciences and medical sciences

[The robotic assistance system.].

Recenti progressi in medicina
The aging of the population is a reality common to the entire Western world, while the time available and human resources are limited. According to many experts, the new robotic technologies could help meet the care needs of the elderly, at home and ...

Transfer learning on T1-weighted images for brain age estimation.

Mathematical biosciences and engineering : MBE
Due to both the hidden nature and the irreversibility of Alzheimers disease (AD), it has become the killer of the elderly and is thus the focus of much attention in the medical field. Radiologists compare the predicted brain age with the ground truth...

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

Journal of Alzheimer's disease : JAD
BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient manage...

PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging.

Aging
Aging biomarkers are the qualitative and quantitative indicators of the aging processes of the human body. Estimation of biological age is important for assessing the physiological state of an organism. The advent of machine learning lead to the deve...

Performance Evaluation of Age Estimation from T1-Weighted Images Using Brain Local Features and CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The age of a subject can be estimated from the brain MR image by evaluating morphological changes in healthy aging. We consider using two-types of local features to estimate the age from T1-weighted images: handcrafted and automatically extracted fea...

Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement.

Restorative neurology and neuroscience
BACKGROUND: Effective human-robot interactions in rehabilitation necessitates an understanding of how these should be tailored to the needs of the human. We report on a robotic system developed as a partner on a 3-D everyday task, using a gamified ap...