Public Health & Policy

Work Force

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

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Unsupervised Non-Rigid Histological Image Registration Guided by Keypoint Correspondences Based on Learnable Deep Features With Iterative Training.

Histological image registration is a fundamental task in histological image analysis. It is challeng...

Boosting Your Context by Dual Similarity Checkup for In-Context Learning Medical Image Segmentation.

The recent advent of in-context learning (ICL) capabilities in large pre-trained models has yielded ...

Knowledge domain and frontier trends of artificial intelligence applied in solid organ transplantation: A visualization analysis.

BACKGROUND: Solid organ transplantation (SOT) is vital for end-stage organ failure but faces challen...

A machine learning model to predict the risk factors causing feelings of burnout and emotional exhaustion amongst nursing staff in South Africa.

BACKGROUND: The demand for quality healthcare is rising worldwide, and nurses in South Africa are un...

Enhancing bowel sound recognition with self-attention and self-supervised pre-training.

Bowel sounds, a reflection of the gastrointestinal tract's peristalsis, are essential for diagnosing...

Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation.

Unsupervised domain adaptation (UDA) has shown impressive performance by improving the generalizabil...

Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.

Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented ...

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...

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

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

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...

Artificial intelligence education in medical imaging: A scoping review.

BACKGROUND: The rise of Artificial intelligence (AI) is reshaping healthcare, particularly in medica...

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...

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 ...

Explicitly diverse visual question generation.

Visual question generation involves the generation of meaningful questions about an image. Although ...

Training machine learning models to detect rare inborn errors of metabolism (IEMs) based on GC-MS urinary metabolomics for diseases screening.

BACKGROUND: Gas chromatography-mass spectrometry (GC-MS) has been shown to be a potentially efficien...

Diagnostic performance of neural network algorithms in skull fracture detection on CT scans: a systematic review and meta-analysis.

BACKGROUND AND AIM: The potential intricacy of skull fractures as well as the complexity of underlyi...

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