Geriatrics

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

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 factors that influence the acceptance of assistive robots by older adults.

Implementation of a structured robotic colorectal curriculum for general surgery residents.

There is increasing demand for colorectal robotic training for general surgery residents. We implemented a robotic colorectal surgery curriculum expecting that it would increase resident exposure to the robotic platform and would increase the number of graduating general surgery residents obtaining a robotic equivalency certificate. The aim of this study is to describe the components of the curric...

Editorial: Can artificial intelligence help us overcome challenges in geriatrics?

Gigapixel end-to-end training using streaming and attention.

Current hardware limitations make it impossible to train convolutional neural networks on gigapixel image inputs directly. Recent developments in weak...

Development of a model for the prediction of biological age.

BACKGROUND AND OBJECTIVE: Rates of aging vary markedly among individuals, and biological age serves as a more reliable predictor of current health sta...

Evolving a Pipeline Approach for Abstract Meaning Representation Parsing Towards Dynamic Neural Networks.

Meaning Representation parsing aims to represent a sentence as a structured, Directed, Acyclic Graph (DAG), in an attempt to extract meaning from text...

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery.

Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurat...

Prediction of Human Organ Toxicity via Artificial Intelligence Methods.

Unpredicted human organ level toxicity remains one of the major reasons for drug clinical failure. There is a critical need for cost-efficient strateg...

Machine learning algorithms for identifying predictive variables of mortality risk following dementia diagnosis: a longitudinal cohort study.

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to...

An end-to-end convolutional neural network for automated failure localisation and characterisation of 3D interconnects.

The advancement in the field of 3D integration circuit technology leads to new challenges for quality assessment of interconnects such as through sili...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The ide...

Lite-SeqCNN: A Light-Weight Deep CNN Architecture for Protein Function Prediction.

The short-and-long range interactions amongst amino-acids in a protein sequence are primarily responsible for the function performed by the protein. R...

Comparison of four machine learning algorithms for a pre-impact fall detection system.

In recent years, real-time health monitoring using wearable sensors has been an active area of research. This paper presents an efficient and low-cost...

Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time.

With an aging population and increased chronic diseases, remote health monitoring has become critical to improving patient care and reducing healthcar...

Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics.

PURPOSE: Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnostic dilemma in clinical practice. To improve the acc...

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. ...

msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.

Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and the auxiliary diagnosis of neurodegenerative dise...

The Etiology of Abnormal TSH in Veterans Cared by a VA Medical Center - One High Serum Thyrotropin is Associated with Higher 5-Years Mortality.

OBJECTIVE: By analyzing the etiology of abnormal TSH in randomly selected veteran patients, we set our heart on improving future clinical care/managem...

The effectiveness of a therapeutic robot, 'Paro', on behavioural and psychological symptoms, medication use, total sleep time and sociability in older adults with dementia: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the effectiveness of a therapeutic robot, 'Paro', on anxiety, agitation, depression, apathy, medication use, total sleep time, ...

Dynamics of redox signaling in aging via autophagy, inflammation, and senescence.

Review paper attempts to explain the dynamic aspects of redox signaling in aging through autophagy, inflammation, and senescence. It begins with ROS s...