Practice Management

Staffing & Scheduling

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

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Evaluating pointwise reliability of machine learning prediction.

Interest in Machine Learning applications to tackle clinical and biological problems is increasing. ...

Semi-supervised learning for medical image classification using imbalanced training data.

BACKGROUND AND OBJECTIVE: Medical image classification is often challenging for two reasons: a lack ...

Impact of robotic single and dual console systems in the training of minimally invasive gynecology surgery (MIGS) fellows.

The advantages of dual console use in robotic surgical education have not been described. The aims o...

Systematic Review of Generative Adversarial Networks (GANs) for Medical Image Classification and Segmentation.

In recent years, generative adversarial networks (GANs) have gained tremendous popularity for variou...

Augmented Humanity: A Systematic Mapping Review.

Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these...

Mini-batch optimization enables training of ODE models on large-scale datasets.

Quantitative dynamic models are widely used to study cellular signal processing. A critical step in ...

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep l...

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset.

OBJECTIVE: To develop an adaptive framework for seizure detection in real-time that is practical to ...

[Artificial intelligence and glaucoma: A literature review].

In recent years, research in artificial intelligence (AI) has experienced an unprecedented surge in ...

Deep learning for retention time prediction in reversed-phase liquid chromatography.

Retention time prediction in high-performance liquid chromatography (HPLC) is the subject of many st...

Sodium adduct formation with graph-based machine learning can aid structural elucidation in non-targeted LC/ESI/HRMS.

Non-targeted screening with LC/ESI/HRMS aims to identify the structure of the detected compounds usi...

Evaluation on the generalization of a learned convolutional neural network for MRI reconstruction.

Recently, deep learning approaches with various network architectures have drawn significant attenti...

Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis.

BACKGROUND: In recent years, robotic rehabilitation devices have often been used for motor training....

Domain generalization on medical imaging classification using episodic training with task augmentation.

Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imag...

DNA-based artificial dendritic cells for in situ cytotoxic T cell stimulation and immunotherapy.

In immunotherapy, ex vivo stimulation of T cells requires significant resources and effort. Here, we...

When unsupervised training benefits category learning.

Humans continuously categorise inputs, but only rarely receive explicit feedback as to whether or no...

Machine learning in systematic reviews: Comparing automated text clustering with Lingo3G and human researcher categorization in a rapid review.

Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus o...

Image-Based Artificial Intelligence in Wound Assessment: A Systematic Review.

Accurately predicting wound healing trajectories is difficult for wound care clinicians due to the ...

London taxi drivers: A review of neurocognitive studies and an exploration of how they build their cognitive map of London.

Licensed London taxi drivers have been found to show changes in the gray matter density of their hip...

A Novel Training and Collaboration Integrated Framework for Human-Agent Teleoperation.

Human operators have the trend of increasing physical and mental workloads when performing teleopera...

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