Geriatrics

Dark-Channel Enhanced-Compensation Net: An end-to-end inner-reflection compensation method for immersive projection system.

Immersive projection display system is widely adopted in virtual reality and various exhibition hall...

Classification of Protein-Binding Sites Using a Spherical Convolutional Neural Network.

The analysis and comparison of protein-binding sites aid various applications in the drug discovery ...

Robotic Esophagectomy Compared With Open Esophagectomy Reduces Sarcopenia within the First Postoperative Year: A Propensity Score-Matched Analysis.

INTRODUCTION: Sarcopenia is a known risk factor for adverse outcomes after esophageal cancer (EC) su...

Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest.

Accurate crash frequency prediction is critical for proactive safety management. The emerging connec...

Multi-perspective region-based CNNs for vertebrae labeling in intraoperative long-length images.

PURPOSE: Effective aggregation of intraoperative x-ray images that capture the patient anatomy from ...

Self-supervised machine learning for live cell imagery segmentation.

Segmenting single cells is a necessary process for extracting quantitative data from biological micr...

End-to-end deep learning model for segmentation and severity staging of anterior cruciate ligament injuries from MRI.

PURPOSE: The purpose of this study was to develop a semi-supervised segmentation and classification ...

Identifying Aortic Stenosis With a Single Parasternal Long-Axis Video Using Deep Learning.

Modeling the adoption of medical wearable devices among the senior adults: Using hybrid SEM-neural network approach.

The world is witnessing an increasing number of senior adult residents who experience health issues....

Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning.

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive declin...

Gait Events Prediction Using Hybrid CNN-RNN-Based Deep Learning Models through a Single Waist-Worn Wearable Sensor.

Elderly gait is a source of rich information about their physical and mental health condition. As an...

Patient-Specific Exercises with the Development of an End-Effector Type Upper Limb Rehabilitation Robot.

End-effector type upper limb rehabilitation robots (ULRRs) are connected to patients at one distal p...

An improved path planning algorithm based on artificial potential field and primal-dual neural network for surgical robot.

Safety and accuracy are essential for path planning in a surgical navigation system. In this paper, ...

NeuroConstruct: 3D Reconstruction and Visualization of Neurites in Optical Microscopy Brain Images.

We introduce NeuroConstruct, a novel end-to-end application for the segmentation, registration, and ...

Application of Deep Convolutional Neural Networks in the Diagnosis of Osteoporosis.

The aim of this study was to assess the possibility of using deep convolutional neural networks (DCN...

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.

The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an ...

A robot-assisted acoustofluidic end effector.

Liquid manipulation is the foundation of most laboratory processes. For macroscale liquid handling, ...

Segmentation of trabecular bone microdamage in Xray microCT images using a two-step deep learning method.

INTRODUCTION: One of the current approaches to improve our understanding of osteoporosis is to study...

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...

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 pe...

An Approach for Fall Prediction Based on Kinematics of Body Key Points Using LSTM.

Many studies have used sensors attached to adults in order to collect signals by which one can carry...