Public Health & Policy

Work Force

Latest AI and machine learning research in work force for healthcare professionals.

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Leveraging Multiple Distinct EEG Training Sessions for Improvement of Spectral-Based Biometric Verification Results.

Most studies on EEG-based biometry recognition report results based on signal databases, with a limi...

Coaching Robots for Older Seniors: Do They Get What They Expect? Insights from an Austrian Study.

To support the increasing number of older people, new (assistive) technologies are constantly being ...

Operational parameter prediction of electrocoagulation system in a rural decentralized water treatment plant by interpretable machine learning model.

Electrocoagulation (EC) is a promising alternative for decentralized drinking water treatment in rur...

Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties.

Machine learning (ML) has become an indispensable tool to predict absorption, distribution, metaboli...

A 2.5D Deep Learning-Based Method for Drowning Diagnosis Using Post-Mortem Computed Tomography.

It is challenging to diagnose drowning in autopsy even with the help of post-mortem multi-slice comp...

The effect of robot-assisted gait training frequency on walking, functional recovery, and quality of life in patients with stroke.

AIM: This study aims to investigate the effects of robot-assisted gait training (RAGT) frequency on ...

SPIDE: A purely spike-based method for training feedback spiking neural networks.

Spiking neural networks (SNNs) with event-based computation are promising brain-inspired models for ...

Effect of robot-assisted gait training on quality of life and depression in neurological impairment: A systematic review and meta-analysis.

OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurologic...

Deep-learning measurement of intracerebral haemorrhage with mixed precision training: a coarse-to-fine study.

AIM: To develop a unified deep-learning-based method for automated intracerebral haemorrhage (ICH) s...

Cost-effectiveness analysis of overground robotic training versus conventional locomotor training in people with spinal cord injury.

BACKGROUND: Few, if any estimates of cost-effectiveness for locomotor training strategies following ...

Ultra-Attention: Automatic Recognition of Liver Ultrasound Standard Sections Based on Visual Attention Perception Structures.

Acquisition of a standard section is a prerequisite for ultrasound diagnosis. For a long time, there...

The identification of interacting brain networks during robot-assisted training with multimodal stimulation.

Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far,...

Diversity Learning Based on Multi-Latent Space for Medical Image Visual Question Generation.

Auxiliary clinical diagnosis has been researched to solve unevenly and insufficiently distributed cl...

Robotics and cybersurgery in ophthalmology: a current perspective.

Ophthalmology is one of the most enriched fields, allowing the domain of artificial intelligence to ...

Effects of automated skill assessment on robotic surgery training.

BACKGROUND: Several automated skill-assessment approaches have been proposed for robotic surgery, bu...

An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation.

Force fields (FFs) for molecular simulation have been under development for more than half a century...

The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks.

Neural activity is often described in terms of population-level factors extracted from the responses...

Transfer learning-based ensemble convolutional neural network for accelerated diagnosis of foot fractures.

The complex shape of the foot, consisting of 26 bones, variable ligaments, tendons, and muscles lead...

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