Staffing & Scheduling

Utilizing Simulation to Evaluate Robotic Skill Acquisition and Learning Decay.

BACKGROUND: We aim to evaluate how new robotic skills are acquired and retained by having participants train and retest using exercises on the robotic platform. We hypothesized that participants with a 3-month break from the robotic platform will have less learning decay and increased retention compared with those with a 6-month break.

Machine Learning in Clinical Trials: A Primer with Applications to Neurology.

We reviewed foundational concepts in artificial intelligence (AI) and machine learning (ML) and discussed ways in which these methodologies may be employed to enhance progress in clinical trials and research, with particular attention to applications in the design, conduct, and interpretation of clinical trials for neurologic diseases. We discussed ways in which ML may help to accelerate the pace ...

Strategy to implement a convolutional neural network based ideal model observer via transfer learning for multi-slice simulated breast CT images.

In this work, we propose a convolutional neural network (CNN)-based multi-slice ideal model observer using transfer learning (TL-CNN) to reduce the re...

Real-Time Sensor Data Profile-Based Deep Learning Method Applied to Open Raceway Pond Microalgal Productivity Prediction.

Microalgal biotechnology holds the potential for renewable biofuels, bioproducts, and carbon capture applications due to unparalleled photosynthetic e...

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 assisted by socially assistive robots (SAR) may have t...

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 success. What has Singapore done to develop an edu...

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 environmental datasets to find solutions that benefit frontl...

Targeting operational regimes of interest in recurrent neural networks.

Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousa...

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 neurosurgeries. We generated updated magnetic resonance ima...

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 globally. At early stages, CVDs appear with minor s...

Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams.

Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery, can be challenging. We aimed to present a full im...

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Four-dimensional (4D) data-independent acquisition (DIA)-based proteomics is a promising technology. However, its full performance is restricted by th...

Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.

Successful clinical trials offer better treatments to current or future patients and advance scientific research. Clinical trials define the target po...

Efficacy of Robot-Assisted and Virtual Reality Interventions on Balance, Gait, and Daily Function in Patients With Stroke: A Systematic Review and Network Meta-analysis.

OBJECTIVE: This study aimed to evaluate the comparative effectiveness and ranking of robot-assisted training, virtual reality, and robot-assisted reha...

Introduction to a Twin Dual-Axis Robotic Platform for Studies of Lower Limb Biomechanics.

This paper presents a twin dual-axis robotic platform system which is designed for the characterization of postural balance under various environmenta...

Discovery of the Lanthipeptide Curvocidin and Structural Insights into its Trifunctional Synthetase CuvL.

Lanthipeptides are ribosomally-synthesized natural products from bacteria featuring stable thioether-crosslinks and various bioactivities. Herein, we ...

A Data-Efficient Deep Learning Strategy for Tissue Characterization via Quantitative Ultrasound: Zone Training.

Deep learning (DL) powered biomedical ultrasound imaging is an emerging research field where researchers adapt the image analysis capabilities of DL a...

A systematic review of video-based educational interventions in robotic surgical training.

As robotic surgical procedures become more prevalent in practice, there is a demand for effective and efficient educational strategies in robotic surg...

Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model.

The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation w...

Cues trigger depiction schemas for robots, as they do for human identities.

Clark and Fischer's three levels of depiction of social robots can be conceptualized as cognitive schemas. When interacting with social robots, humans...