Geriatrics

Detection of the Relationship between the Multi-Dimensional Data Sets of Serially Measured Blood Pressure and the Future Risk of Death in Healthy Elderly Japanese Population.

AIMS: Whether the multi-dimensional data of serially measured blood pressure contains information fo...

An artificial-intelligence-based age-specific template construction framework for brain structural analysis using magnetic resonance images.

It is an essential task to construct brain templates and analyze their anatomical structures in neur...

Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data.

Brain structural morphology varies over the aging trajectory, and the prediction of a person's age u...

E-Cardiac Care: A Comprehensive Systematic Literature Review.

The Internet of Things (IoT) is a complete ecosystem encompassing various communication technologies...

Automated photo-aligned liquid crystal elastomer film fabrication with a low-tech, home-built robotic workstation.

Laboratory procedures are often considered so unique that automating them is not economically justif...

Association of artificial intelligence use and the retention of elderly caregivers: A cross-sectional study based on empowerment theory.

AIM: The purpose of this study is to investigate how the use of artificial intelligence is associate...

Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction.

BACKGROUND: Gait recognition has been applied in the prediction of the probability of elderly flat g...

Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review.

Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical ...

sEMG-Based Gain-Tuned Compliance Control for the Lower Limb Rehabilitation Robot during Passive Training.

The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems...

Identifying the presence and severity of dementia by applying interpretable machine learning techniques on structured clinical records.

BACKGROUND: Dementia develops as cognitive abilities deteriorate, and early detection is critical fo...

Generalizable deep learning model for early Alzheimer's disease detection from structural MRIs.

Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In ...

How feasible is end-to-end deep learning for clinical neuroimaging?

Monitoring and early warning of a metal mine tailings pond based on a deep learning bidirectional recurrent long and short memory network.

The effective monitoring and early warning capability of metal mine tailings ponds can improve the a...

Long-distance Robot-assisted Teleoperation: Every Millisecond Counts.

Human-Robot Cooperative Strength Training Based on Robust Admittance Control Strategy.

A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. St...

Delirium screening in an acute care setting with a machine learning classifier based on routinely collected nursing data: A model development study.

Delirium screening in acute care settings is a resource intensive process with frequent deviations f...

Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules.

In recent years, the non-biological applications of DNA molecules have made considerable progress; m...

Perioperative outcomes following robot-assisted partial nephrectomy in elderly patients.

OBJECTIVE: To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in ...

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images.

Detection of a brain tumor in the early stages is critical for clinical practice and survival rate. ...

Class-Imbalanced Deep Learning via a Class-Balanced Ensemble.

Class imbalance is a prevalent phenomenon in various real-world applications and it presents signifi...

GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention.

Channel attention mechanisms have been commonly applied in many visual tasks for effective performan...