Public Health & Policy

Work Force

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

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Evaluating machine- and deep learning approaches for artifact detection in infant EEG: classifier performance, certainty, and training size effects.

Electroencephalography (EEG) is essential for studying infant brain activity but is highly susceptib...

Large-Scale Non-Adiabatic Dynamics Simulation Based on Machine Learning Hamiltonian and Force Field: The Case of Charge Transport in Monolayer MoS.

We present an efficient and reliable large-scale non-adiabatic dynamics simulation method based on m...

Unsupervised post-training learning in spiking neural networks.

The human brain is a dynamic system that is constantly learning. It employs a combination of various...

Reconstruction of partially obscured objects with a physics-driven self-training neural network.

We investigate artificial-intelligence-supported in-line holographic imaging with coherent terahertz...

Strategic tips to successfully undertake research: a comprehensive roadmap for medical trainees.

Engaging in research during medical training is crucial for fostering critical thinking, enhancing c...

Private Data Incrementalization: Data-Centric Model Development for Clinical Liver Segmentation.

Machine Learning models, more specifically Artificial Neural Networks, are transforming medical imag...

Virtual Enumerator's Training for Time and Motion Studies Using AI Scenarios.

This paper presents the implementation of a virtual training program for enumerators conducting Time...

German Medical NER with BERT and LLMs: The Impact of Training Data Size.

Named Entity Recognition (NER) in the medical domain often presents significant challenges due to th...

Evaluating Generative AI in Mental Health: Systematic Review of Capabilities and Limitations.

BACKGROUND: The global shortage of mental health professionals, exacerbated by increasing mental hea...

Exploring the Opportunities and Challenges of Healthcare Innovation in UK Higher Education: A Narrative Review.

: The healthcare sector is under increasing pressure due to an ageing population, rising multimorbid...

A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing.

Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumo...

Electromechanical-assisted training for walking after stroke.

RATIONALE: Walking difficulties are common after a stroke. During rehabilitation, electromechanical ...

Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies.

Metadata, or "data about data," is essential for organizing, understanding, and managing large-scale...

Generating diversity and securing completeness in algorithmic retrosynthesis.

Chemical synthesis planning has considerably benefited from advances in the field of machine learnin...

AI-IoT based smart agriculture pivot for plant diseases detection and treatment.

There are some key problems faced in modern agriculture that IoT-based smart farming. These problems...

Revisiting Machine Learning Potentials for Silicate Glasses: The Missing Role of Dispersion Interactions.

Machine learning interatomic potentials (MLIPs) offer a promising alternative to traditional force f...

Active Learning FEP: Impact on Performance of AL Protocol and Chemical Diversity.

Active learning using models built on binding potency predictions from free energy perturbation (AL-...

Evaluating a Convolutional Neural Network Noise Reduction Method When Applied to CT Images Reconstructed Differently Than Training Data.

OBJECTIVE: The aim of this study was to evaluate a narrowly trained convolutional neural network (CN...

A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability.

The major challenges in drug development stem from frequent structure-activity cliffs and unknown dr...

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