Geriatrics

: The Impact of Obesity in Patients Undergoing Robotic Partial Nephrectomy by Rosen et al. (J Endourol 2019;33(6):431-437; DOI: 10.1089/end.2019.0018).

Evaluation of Balance and Fall Risk in Patients with Plantar Fasciitis Syndrome.

OBJECTIVES: In this study, we aimed to investigate plantar fasciitis syndrome on balance and the ris...

IoT-Enabled Dual-Arm Motion Capture and Mapping for Telerobotics in Home Care.

With the paradigm shift from hospital-centric healthcare to home-centric healthcare in Healthcare 4....

Characterization of the complete chloroplast genome of (Caprifoliaceae), a long history herb species plant from China.

is a common ornamental and medicinal plant in North America and East Asia. In this study, the compl...

Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos.

The present study aimed to conduct a real-time automatic analysis of two important surgical phases, ...

Genome-wide prediction and prioritization of human aging genes by data fusion: a machine learning approach.

BACKGROUND: Machine learning can effectively nominate novel genes for various research purposes in t...

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic...

Wearable Fall Detector Using Recurrent Neural Networks.

Falls have become a relevant public health issue due to their high prevalence and negative effects i...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk i...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheim...

Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network.

3D medical image registration is of great clinical importance. However, supervised learning methods ...

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lac...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progress...

Qualitative, Exploratory, and Multidimensional Study of Telepresence Robots for Overcoming Social Isolation of Children and Adolescents Hospitalized in Onco-Hematology.

Treatment of pediatric cancers and hematological malignancies requires long periods of isolation in...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

The automatic recognition of human falls is currently an important topic of research for the compute...

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative d...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume ...

MCADNNet: Recognizing Stages of Cognitive Impairment through Efficient Convolutional fMRI and MRI Neural Network Topology Models.

Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and ...

Voice-Controlled Intelligent Personal Assistants to Support Aging in Place.

BACKGROUND/OBJECTIVES: Many older adults wish to age in place, and voice-controlled intelligent pers...

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks.

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a pred...

Granger causality analysis in combination with directed network measures for classification of MS patients and healthy controls using task-related fMRI.

Several studies have already assessed brain network variations in multiple sclerosis (MS) patients a...