Practice Management

Staffing & Scheduling

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

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Showing 1072-1092 of 6,146 articles
Artificial intelligence-based video monitoring of movement disorders in the elderly: a review on current and future landscapes.

Due to global ageing, the burden of chronic movement and neurological disorders (Parkinson's disease...

Can biased search results change people's opinions about anything at all? a close replication of the Search Engine Manipulation Effect (SEME).

In previous experiments we have conducted on the Search Engine Manipulation Effect (SEME), we have f...

A paradigm shift?-On the ethics of medical large language models.

After a wave of breakthroughs in image-based medical diagnostics and risk prediction models, machine...

Within-Session Reliability of fNIRS in Robot-Assisted Upper-Limb Training.

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted re...

PSE-Net: Channel pruning for Convolutional Neural Networks with parallel-subnets estimator.

Channel Pruning is one of the most widespread techniques used to compress deep neural networks while...

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening].

INTRODUCTION: The recruitment step of all clinical trials is time consuming, harsh and generate extr...

Artificial intelligence tools for optimising recruitment and retention in clinical trials: a scoping review protocol.

INTRODUCTION: In recent years, the influence of artificial intelligence technology on clinical trial...

Work With ChatGPT, Not Against: 3 Teaching Strategies That Harness the Power of Artificial Intelligence.

BACKGROUND: Technological advances have expanded nursing education to include generative artificial ...

Improving Vessel Segmentation with Multi-Task Learning and Auxiliary Data Available Only During Model Training.

Liver vessel segmentation in magnetic resonance imaging data is important for the computational anal...

PPII-AEAT: Prediction of protein-protein interaction inhibitors based on autoencoders with adversarial training.

Protein-protein interactions (PPIs) have shown increasing potential as novel drug targets. The desig...

Improving the performance of machine learning penicillin adverse drug reaction classification with synthetic data and transfer learning.

BACKGROUND: Machine learning may assist with the identification of potentially inappropriate penicil...

Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction.

The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-res...

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Skin cancer, including the highly lethal malignant melanoma, poses a significant global health chall...

Effectiveness of designing a knowledge-based artificial intelligence chatbot system into a nursing training program: A quasi-experimental design.

BACKGROUND: Chatbots have gained popularity in the healthcare industry due to their ability to provi...

Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review.

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care...

Performance of Two Artificial Intelligence Generative Language Models on the Orthopaedic In-Training Examination.

BACKGROUND: Artificial intelligence (AI) generative large language models are powerful and increasin...

Source-free unsupervised domain adaptation: A survey.

Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tacklin...

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clini...

A Combination Model of Shifting Joint Angle Changes With 3D-Deep Convolutional Neural Network to Recognize Human Activity.

Research in the field of human activity recognition is very interesting due to its potential for var...

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