Staffing & Scheduling

Active control time: an objective performance metric for trainee participation in robotic surgery.

Trainee participation and progression in robotic general surgery remain poorly defined. Computer-ass...

Training Neural Network Models Using Molecular Dynamics Simulation Results to Efficiently Predict Cyclic Hexapeptide Structural Ensembles.

Cyclic peptides have emerged as a promising class of therapeutics. However, their design remains ch...

Exoskeleton Training Modulates Complexity in Movement Patterns and Cortical Activity in Able-Bodied Volunteers.

Robot-aided gait training (RAGT) plays a crucial role in providing high-dose and high-intensity task...

Intentional enterotomies: validation of a novel robotic surgery training exercise.

While laparoscopic simulation-based training is a well-established component of general surgery trai...

Learning in an era of uncertainty in Singapore: diversity, lifelong learning, inspiration and paradigm shift.

This is an era of uncertainty, during which adaptability is a key capability to survival and future ...

Research Participant Selection Bias in the Workshop Using Socially Assistive Robots for Older Adults and Its Effect on Population Representativeness.

Every research participant has their own personality characteristics. For example, older adults assi...

LoyalDE: Improving the performance of Graph Neural Networks with loyal node discovery and emphasis.

Recent years have witnessed an increasing focus on graph-based semi-supervised learning with Graph N...

Artificial intelligence in the in vitro fertilization laboratory: a review of advancements over the last decade.

The integration of artificial intelligence (AI) and deep learning algorithms into medical care has b...

Interpretable Machine Learning Models for Phase Prediction in Polymerization-Induced Self-Assembly.

While polymerization-induced self-assembly (PISA) has become a preferred synthetic route toward amph...

Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions.

There is a growing need to apply geospatial artificial intelligence analysis to disparate environmen...

The effects of Robot-assisted gait training and virtual reality on balance and gait in stroke survivors: A randomized controlled trial.

BACKGROUND: Stroke survivors often experience balance and gait problems, which can affect their qual...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. Thi...

Sustainability of translator training in higher education.

The United Nations has set a Sustainable Development Goal in education to be met hopefully by 2030. ...

Targeting operational regimes of interest in recurrent neural networks.

Neural computations emerge from local recurrent neural circuits or computational units such as corti...

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation.

Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurg...

A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening.

Over the past few years, many machine learning-based scoring functions for predicting the binding of...

Judging facts, judging norms: Training machine learning models to judge humans requires a modified approach to labeling data.

As governments and industry turn to increased use of automated decision systems, it becomes essentia...

ChatGPT in Medical Education: a Paradigm Shift or a Dangerous Tool?

Show Your Work: Responsible Model Reporting in Health Care Artificial Intelligence.

Standardized and thorough model reporting is an integral component in the development and deployment...

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images.

PURPOSE: To improve automated lung segmentation on 2D lung MR images using balanced augmentation and...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality g...