Practice Management

Staffing & Scheduling

Latest AI and machine learning research in staffing & scheduling for healthcare professionals.

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Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.

Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predic...

The analysis of urban collaborative governance in public health emergencies with fuzzy theory based on BP algorithm.

This study seeks to improve urban supply chain management and collaborative governance in the contex...

BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.

In the past several years, a few cervical Pap smear datasets have been published for use in clinical...

Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training.

Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of c...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support ep...

Explainable AI improves task performance in human-AI collaboration.

Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one ...

A randomized controlled trial on anonymizing reviewers to each other in peer review discussions.

Many peer-review processes involve reviewers submitting their independent reviews, followed by a dis...

The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children.

The rising prevalence of myopia is a significant global health concern. Atropine eye drops are comm...

Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.

Neuroimaging techniques including functional magnetic resonance imaging (fMRI) and electroencephalog...

Large language models facilitating modern molecular biology and novel drug development.

The latest breakthroughs in information technology and biotechnology have catalyzed a revolutionary ...

Predicting upper limb motor recovery in subacute stroke patients via fNIRS-measured cerebral functional responses induced by robotic training.

BACKGROUND: Neural activation induced by upper extremity robot-assisted training (UE-RAT) helps char...

Machine learning analysis of factors affecting college students' academic performance.

This study aims to explore various key factors influencing the academic performance of college stude...

Development of a Virtual Robot Rehabilitation Training System for Children with Cerebral Palsy: An Observational Study.

This paper presents the development of a robotic system for the rehabilitation and quality of life i...

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Medical image analysis has significantly benefited from advancements in deep learning, particularly ...

Reproducibility and quality of hypertrophy-related training plans generated by GPT-4 and Google Gemini as evaluated by coaching experts.

Large Language Models (LLMs) are increasingly utilized in various domains, including the generation ...

Target informed client recruitment for efficient federated learning in healthcare.

BACKGROUND: Modern machine learning and deep learning methods have been widely incorporated in decis...

An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontology-Enhanced Large Language Models: Development Study.

BACKGROUND: Rare diseases affect millions worldwide but sometimes face limited research focus indivi...

Revolutionizing market surveillance: customer relationship management with machine learning.

In the telecommunications industry, predicting customer churn is essential for retaining clients and...

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