Public Health & Policy

Work Force

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

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Specialist hybrid models with asymmetric training for malaria prevalence prediction.

Malaria is a common and serious disease that primarily affects developing countries and its spread i...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

An increasing and aging patient population poses a growing burden on healthcare professionals. Autom...

An Overview of Robotic Colorectal Surgery Adoption and Training in Brazil.

Robotic surgical systems have rapidly become integrated into colorectal surgery practice in recent ...

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and e...

Assessment of robotic telesurgery system among surgeons: a single-center study.

The field of robotic-assisted surgery is expanding rapidly; therefore, future robotic surgeons will ...

Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials.

OBJECTIVES: Numbers of research have reported the usage of robot-assisted gait training for walking ...

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data.

Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity p...

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation.

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts rangin...

A self-supervised deep learning method for data-efficient training in genomics.

Deep learning in bioinformatics is often limited to problems where extensive amounts of labeled data...

Adv-BDPM: Adversarial attack based on Boundary Diffusion Probability Model.

Deep neural networks have become increasingly significant in our daily lives due to their remarkable...

SCANet: A Unified Semi-Supervised Learning Framework for Vessel Segmentation.

Automatic subcutaneous vessel imaging with near-infrared (NIR) optical apparatus can promote the acc...

Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot.

Real world settings are seldomly just composed of level surfaces and stairs are frequently encounter...

Effect of Flattened Structures of Molecules and Materials on Machine Learning Model Training.

A key aspect of producing accurate and reliable machine learning models for the prediction of proper...

Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM).

The landscape of surgical training is rapidly evolving with the advent of artificial intelligence (A...

Human Factors Considerations for Quantifiable Human States in Physical Human-Robot Interaction: A Literature Review.

As the global population rapidly ages with longer life expectancy and declining birth rates, the nee...

Application of cluster repeated mini-batch training method to classify electroencephalography for grab and lift tasks.

Modern deep neural network training is based on mini-batch stochastic gradient optimization. While u...

Robotic Medtronic Hugo™ RAS System Is Now Reality: Introduction to a New Simulation Platform for Training Residents.

The use of robotic surgery (RS) in urology has grown exponentially in the last decade, but RS traini...

Robotic locomotor training in a low-resource setting: a randomized pilot and feasibility trial.

PURPOSE: Activity-based Training (ABT) represents the current standard of neurological rehabilitatio...

Bridged adversarial training.

Adversarial robustness is considered a required property of deep neural networks. In this study, we ...

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