Public Health & Policy

Work Force

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

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A stochastic modeling approach for analyzing water resources systems.

Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of th...

Deep learning for colon cancer histopathological images analysis.

Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours. Unfortunat...

Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI)....

A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations.

MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dic...

A dual-channel language decoding from brain activity with progressive transfer training.

When we view a scene, the visual cortex extracts and processes visual information in the scene throu...

Robot-assisted gait training in individuals with spinal cord injury: A systematic review for the clinical effectiveness of Lokomat.

BACKGROUND: Spinal cord injury (SCI) is a critical medical condition that causes numerous impairment...

Computed Tomography Angiography under Deep Learning in the Treatment of Atherosclerosis with Rapamycin.

The clinical characteristics and vascular computed tomography (CT) imaging characteristics of patien...

Disease ontologies for knowledge graphs.

BACKGROUND: Data integration to build a biomedical knowledge graph is a challenging task. There are ...

Analysis of Body Behavior Characteristics after Sports Training Based on Convolution Neural Network.

The use of artificial intelligence technology to analyze human behavior is one of the key research t...

Three-stage segmentation of lung region from CT images using deep neural networks.

BACKGROUND: Lung region segmentation is an important stage of automated image-based approaches for t...

Robot-Assisted Gait Training in Patients with Multiple Sclerosis: A Randomized Controlled Crossover Trial.

Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly...

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization.

Unmasking the decision making process of machine learning models is essential for implementing diagn...

Fast deep neural correspondence for tracking and identifying neurons in using semi-synthetic training.

We present an automated method to track and identify neurons in , called 'fast Deep Neural Correspon...

Health Recognition Algorithm for Sports Training Based on Bi-GRU Neural Networks.

The healthcare benefits associated with regular physical activity recognition and monitoring have be...

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