Practice Management

Staffing & Scheduling

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

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Showing 1807-1827 of 6,167 articles
A self-training teacher-student model with an automatic label grader for abdominal skeletal muscle segmentation.

Deep learning on a limited number of labels/annotations is a challenging task for medical imaging an...

Monocular Depth Estimation Using Deep Learning: A Review.

In current decades, significant advancements in robotics engineering and autonomous vehicles have im...

Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy.

Adversarial robustness has become a central goal in deep learning, both in the theory and the practi...

Convolutional Neural Networks and Heuristic Methods for Crowd Counting: A Systematic Review.

The crowd counting task has become a pillar for crowd control as it provides information concerning ...

Classification of COVID-19 from tuberculosis and pneumonia using deep learning techniques.

Deep learning provides the healthcare industry with the ability to analyse data at exceptional speed...

Artificial intelligence: Training the trainer.

Including artificial intelligence in haematological education is compulsory but should not be limite...

Design, Fabrication, and Performance Test of a New Type of Soft-Robotic Gripper for Grasping.

This investigation presents a novel soft-robotic pneumatic gripper that consists of three newly prop...

A personalized deep learning denoising strategy for low-count PET images.

. Deep learning denoising networks are typically trained with images that are representative of the ...

A unified parameter model based on machine learning for describing microbial transport in porous media.

The transport and retention of microorganisms are typically described using attachment/detachment an...

A multi-model fusion algorithm as a real-time quality control tool for small shift detection.

BACKGROUND: Patient-based real-time quality control (PBRTQC), a complement to traditional QC, may el...

Early Termination Based Training Acceleration for an Energy-Efficient SNN Processor Design.

In this paper, we present a novel early termination based training acceleration technique for tempor...

Inverse folding based pre-training for the reliable identification of intrinsic transcription terminators.

It is well-established that neural networks can predict or identify structural motifs of non-coding ...

Generalising from conventional pipelines using deep learning in high-throughput screening workflows.

The study of complex diseases relies on large amounts of data to build models toward precision medic...

Construction of Cognitive Model of Family Education Decision-Making Based on Neural Network.

Family's academic cognition influences the family's academic concept, rearing fashion, and academic ...

Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions.

There remains a limited emphasis on the use beyond the research domain of artificial intelligence (A...

Adjustable Parameters and the Effectiveness of Adjunct Robot-Assisted Gait Training in Individuals with Chronic Stroke.

The aims of this study were (1) to compare the effect of robot-assisted gait orthosis (RAGO) plus co...

KAT: A Knowledge Adversarial Training Method for Zero-Order Takagi-Sugeno-Kang Fuzzy Classifiers.

While input or output-perturbation-based adversarial training techniques have been exploited to enha...

Design of Travel Route Identification and Scheduling System Based on Artificial Intelligence-Aided Image Segmentation.

This study designs a travel recognition and scheduling system using artificial intelligence and imag...

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