Practice Management

Staffing & Scheduling

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

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Uncertainty modeling for inductive knowledge graph embedding.

In the process of refining Knowledge Graphs (KGs), new entities emerge, and old entities evolve, whi...

Enhancing Medical Student Engagement Through Cinematic Clinical Narratives: Multimodal Generative AI-Based Mixed Methods Study.

BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics du...

Real-Time Analytics and AI for Managing No-Show Appointments in Primary Health Care in the United Arab Emirates: Before-and-After Study.

BACKGROUND: Primary health care (PHC) services face operational challenges due to high patient volum...

Automatic medical report generation based on deep learning: A state of the art survey.

With the increasing popularity of medical imaging and its expanding applications, posing significant...

Enhancing lipid identification in LC-HRMS data through machine learning-based retention time prediction.

The comprehensive identification of peaks in untargeted lipidomics using LC-MS/MS remains a signific...

Artificial Intelligence-Powered Training Database for Clinical Thinking: App Development Study.

BACKGROUND: With the development of artificial intelligence (AI), medicine has entered the era of in...

Effectiveness of robot-assisted task-oriented training intervention for upper limb and daily living skills in stroke patients: A meta-analysis.

PURPOSE: Stroke is one of the leading causes of acquired disability in adults in high-income countri...

IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-Training.

In medical Vision-Language Pre-training (VLP), significant work focuses on extracting text and image...

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...

CS-QCFS: Bridging the performance gap in ultra-low latency spiking neural networks.

Spiking Neural Networks (SNNs) are at the forefront of computational neuroscience, emulating the nua...

A Systematic Review of Features Forecasting Patient Arrival Numbers.

Adequate nurse staffing is crucial for quality healthcare, necessitating accurate predictions of pat...

Identity Model Transformation for boosting performance and efficiency in object detection network.

Modifying the structure of an existing network is a common method to further improve the performance...

Improving the performance of echo state networks through state feedback.

Reservoir computing, using nonlinear dynamical systems, offers a cost-effective alternative to neura...

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...

Whither bias goes, I will go: An integrative, systematic review of algorithmic bias mitigation.

Machine learning (ML) models are increasingly used for personnel assessment and selection (e.g., res...

Towards safe and reliable deep learning for lung nodule malignancy estimation using out-of-distribution detection.

Artificial Intelligence (AI) models may fail or suffer from reduced performance when applied to unse...

Utilizing Artificial neural networks (ANN) to regulate Smart cities for sustainable Urban Development and Safeguarding Citizen rights.

The advent of smart cities has brought about a paradigm shift in urban management and citizen engage...

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 ...

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