Geriatrics

The Use of Robotics in Dementia Care: An Ethical Perspective.

Dementia and other related diseases are becoming increasingly diagnosed and are placing a serious strain on the healthcare system. Robotic technology research is currently underway to provide the much needed support to patients, caregivers, and health providers. This includes examining the ethical implications of robots use in healthcare. This scoping review explores the current state of the liter...

Physiological Assessment of Delirium Severity: The Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

OBJECTIVES: Delirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a tool that can help close this diagnostic gap: the Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions.

BACKGROUND: Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associ...

Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer's Disease.

BACKGROUND: In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in descri...

Chronic Beneficial Effect of Makeup Therapy on Cognitive Function of Dementia and Facial Appearance Analyzed by Artificial Intelligence Software.

BACKGROUND: Makeup greatly impacts normal social lives but can also be a non-pharmacological form of therapy for dementia.

A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transiti...

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.

The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make f...

Effects of Exercise-Diet Therapy on Cognitive Function in Healthy Elderly People Evaluated by Deep Learning Based on Basic Blood Test Data.

BACKGROUND: Recent studies reported that vascular cognitive impairment in the elderly caused by arteriosclerosis plays an important role in cognitive ...

Applications and Challenges of Machine Learning Methods in Alzheimer's Disease Multi-Source Data Analysis.

BACKGROUND: Recent development in neuroimaging and genetic testing technologies have made it possible to measure pathological features associated with...

Educational Program Using Robots for Preventing Cognitive Decline of Elderly Persons.

An expected surge of dementia patients in Japan indicates a pressing need to establish countermeasures. As described herein, by developing an educatio...

[The accuracy and influencing factors of sleep staging based on single-channel EEG via a deep neural network].

To investigate theaccuracy of artificial intelligence sleep staging model in patients with habitual snoring and obstructive sleep apnea hypopnea synd...

[Exploration of applying machine learning in establishment of vitamin D classifiers among Chinese elderly].

To establish vitamin D classification models for Chinese elderly using machine learning techniques. Based on the datasets of 2010-2012 Chinese nutri...

Construction of a 5-feature gene model by support vector machine for classifying osteoporosis samples.

Osteoporosis is a progressive bone disease in the elderly and lacks an effective classification method of patients. This study constructed a gene sign...

Augmenting Osteoporosis Imaging with Machine Learning.

PURPOSE OF REVIEW: In this paper, we discuss how recent advancements in image processing and machine learning (ML) are shaping a new and exciting era ...

Effective End-to-End Deep Learning Process in Medical Imaging Using Independent Task Learning: Application for Diagnosis of Maxillary Sinusitis.

PURPOSE: This study aimed to propose an effective end-to-end process in medical imaging using an independent task learning (ITL) algorithm and to eval...

Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data.

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder characterized by memory loss and cognitive decline. Early detection and acc...

Simple Convolutional-Based Models: Are They Learning the Task or the Data?

Convolutional neural networks (CNNs) evolved from Fukushima's neocognitron model, which is based on the ideas of Hubel and Wiesel about the early stag...

Automatic segmentation of paravertebral muscles in abdominal CT scan by U-Net: The application of data augmentation technique to increase the Jaccard ratio of deep learning.

Sarcopenia, characterized by a decline of skeletal muscle mass, has emerged as an important prognostic factor for cancer patients. Trunk computed tomo...

[Retinal Imaging as Potential Biomarkers for Dementia].

Alzheimer's disease (AD) is a leading cause of dementia, and the current diagnostic methods of AD, such as positron emission tomography imaging, have ...

Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders.

Extracellular recordings are severely contaminated by a considerable amount of noise sources, rendering the denoising process an extremely challenging...