Public Health & Policy

Work Force

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

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Rehabilitation Treatment of Muscle Strain in Athlete Training under Intelligent Intervention.

With the development of artificial intelligence technology in the medical field, clinical trials usi...

Cramér-Rao bound-informed training of neural networks for quantitative MRI.

PURPOSE: To improve the performance of neural networks for parameter estimation in quantitative MRI,...

Effect Evaluation of Electronic Health PDCA Nursing in Treatment of Childhood Asthma with Artificial Intelligence.

Asthma in children has a long duration and is prone to recurring attacks. Children will feel chest t...

Differentially Private Singular Value Decomposition for Training Support Vector Machines.

Support vector machine (SVM) is an efficient classification method in machine learning. The traditio...

A data-driven approach to characterizing nonlinear elastic behavior of soft materials.

The Autoprogressive (AutoP) method is a data-driven inverse method that leverages finite element ana...

Research on Application of Sports Training Performance Prediction Based on Convolutional Neural Network.

In order to improve the prediction effect of sports training performance and improve the effect of s...

Nonlinear Network Speech Recognition Structure in a Deep Learning Algorithm.

As a result of the fast rise of globalization, people in China are learning English at a rapid pace....

Word-level text highlighting of medical texts for telehealth services.

The medical domain is often subject to information overload. The digitization of healthcare, constan...

Investigation of Effectiveness of Shuffled Frog-Leaping Optimizer in Training a Convolution Neural Network.

One of the leading algorithms and architectures in deep learning is Convolution Neural Network (CNN)...

Effectiveness of individualized training based on force-velocity profiling on physical function in older men.

The study aimed to investigate the effectiveness of an individualized power training program based o...

Many-Body Neural Network-Based Force Field for Structure-Based Coarse-Graining of Water.

High-fidelity results from atomistic simulations can only be obtained by using accurate force-field ...

Action Recognition, Tracking, and Optimization Analysis of Training Process Based on the Support Vector Regression Model.

In order to study the action recognition, tracking, and optimization of the training process based o...

A Robotic System to Deliver Multiple Physically Bimanual Tasks via Varying Force Fields.

Individuals with physical limb disabilities are often restricted to perform activities of daily life...

Decoding lip language using triboelectric sensors with deep learning.

Lip language is an effective method of voice-off communication in daily life for people with vocal c...

Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

In this study, a wavelet recurrent fuzzy neural network is used to conduct in-depth research and ana...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scal...

The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale's 18th problem.

Deep learning (DL) has had unprecedented success and is now entering scientific computing with full ...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accura...

Overground robotic training effects on walking and secondary health conditions in individuals with spinal cord injury: systematic review.

Overground powered lower limb exoskeletons (EXOs) have proven to be valid devices in gait rehabilita...

A Contrastive Predictive Coding-Based Classification Framework for Healthcare Sensor Data.

Supervised learning technologies have been used in medical-data classification to improve diagnosis ...

A 3D Printed Soft Robotic Hand With Embedded Soft Sensors for Direct Transition Between Hand Gestures and Improved Grasping Quality and Diversity.

In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors, intend...

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