Geriatrics

Perioperative Red Cell Line Trend following Robot-Assisted Radical Prostatectomy for Prostate Cancer.

Background and Objective: Blood loss represents a long-standing concern of radical prostatectomy (RP). This study aimed to assess how red line cell values changed following robot-assisted radical prostatectomy (RARP) for prostate cancer (PCa). Materials and Methods: The blood panels of 453 consecutive PCa patients undergoing RARP at a single tertiary academic referral center, from September 2020 t...

Staging Paro: The care of making robot(s) care.

Paro, a baby seal robot, is arguably the best-known care robot worldwide. Its clinical effects on people with special needs have been studied for more than twenty years by multidisciplinary teams. However, there are very few studies of Paro 'in the wild', inserted in the routines and pressures of a care home, which is supposed to be Paro's natural environment. Based on fieldwork in a French public...

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 for predicting the future risk of death in elderly i...

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 neurological and cognitive science. Generally, templat...

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 using brain morphological features can help the det...

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 justified - time and resources invested in designing, bu...

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 associated with the retention of elderly caregivers.

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 observations. However, these diagnoses are not per...

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 this study, we have developed a new approach based...

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 for effective preventive interventions. However, mai...

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 of insufficient physiological information and uns...

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. Stroke survivors can effectively train muscle streng...

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 from screening protocols. A predictive model relyin...

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; most of these applications were performed in vitro,...

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

Class imbalance is a prevalent phenomenon in various real-world applications and it presents significant challenges to model learning, including deep ...

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

Channel attention mechanisms have been commonly applied in many visual tasks for effective performance improvement. It is able to reinforce the inform...

De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models.

Electronic Medical Records (EMRs) contain clinical narrative text that is of great potential value to medical researchers. However, this information i...

A Care Robot with Ethical Sensing System for Older Adults at Home.

Many studies have explored emotional and mental services that robots can provide for older adults, such as offering them daily conversation, news, mus...

A deep learning model for detection of Alzheimer's disease based on retinal photographs: a retrospective, multicentre case-control study.

BACKGROUND: There is no simple model to screen for Alzheimer's disease, partly because the diagnosis of Alzheimer's disease itself is complex-typicall...

Sam's Net: A Self-Augmented Multistage Deep-Learning Network for End-to-End Reconstruction of Limited Angle CT.

Limited angle reconstruction is a typical ill-posed problem in computed tomography (CT). Given incomplete projection data, images reconstructed by con...