Public Health & Policy

Work Force

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

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Generative adversarial networks with mixture of t-distributions noise for diverse image generation.

Image generation is a long-standing problem in the machine learning and computer vision areas. In or...

Artificial intelligence and the future of psychiatry: Insights from a global physician survey.

BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial inte...

Muscle endurance time estimation during isometric training using electromyogram and supervised learning.

UNLABELLED: Constant-force isometric muscle training is useful for increasing the maximal strength ,...

Semi-supervised Training Data Selection Improves Seizure Forecasting in Canines with Epilepsy.

OBJECTIVE: Conventional selection of pre-ictal EEG epochs for seizure prediction algorithm training ...

Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training.

Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve t...

Clinical non-superiority of technology-assisted gait training with body weight support in patients with subacute stroke: A meta-analysis.

BACKGROUND: Technology-assisted gait training (TAGT) with body weight support (BWS) has been designe...

A Virtual Counseling Application Using Artificial Intelligence for Communication Skills Training in Nursing Education: Development Study.

BACKGROUND: The ability of nursing undergraduates to communicate effectively with health care provid...

Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots.

In the process of rehabilitation training for stroke patients, the rehabilitation effect is positive...

Harnessing behavioral diversity to understand neural computations for cognition.

With the increasing acquisition of large-scale neural recordings comes the challenge of inferring th...

Deep-Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size.

BACKGROUND: The dependence of deep-learning (DL)-based segmentation accuracy of brain MRI on the tra...

Training for Walking Efficiency With a Wearable Hip-Assist Robot in Patients With Stroke: A Pilot Randomized Controlled Trial.

Background and Purpose- The purpose of this study was to investigate the effects of gait training wi...

Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method.

BACKGROUND: Current lung cancer screening guidelines use mean diameter, volume or density of the lar...

A microsurgical robot research platform for robot-assisted microsurgery research and training.

PURPOSE: Ocular surgery, ear, nose and throat surgery and neurosurgery are typical types of microsur...

Dual Model Medical Invoices Recognition.

Hospitals need to invest a lot of manpower to manually input the contents of medical invoices (nearl...

Graph Classification of Molecules Using Force Field Atom and Bond Types.

Classification of the biological activities of chemical substances is important for developing new m...

Artificial intelligence reveals environmental constraints on colour diversity in insects.

Explaining colour variation among animals at broad geographic scales remains challenging. Here we de...

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.

We present a machine learning approach to automated force field development in dissipative particle ...

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