Staffing & Scheduling

Comparison of a Deep Learning-Based Pose Estimation System to Marker-Based and Kinect Systems in Exergaming for Balance Training.

Using standard digital cameras in combination with deep learning (DL) for pose estimation is promising for the in-home and independent use of exercise games (exergames). We need to investigate to what extent such DL-based systems can provide satisfying accuracy on exergame relevant measures. Our study assesses temporal variation (i.e., variability) in body segment lengths, while using a Deep Learn...

Statistical stopping criteria for automated screening in systematic reviews.

Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. Machines and humans work together, with humans providing training data, and the machine optimising the documents that the humans screen. This enables the identification of all relevant documents after viewing only a fraction of the total documents. Ho...

Detecting cells in intravital video microscopy using a deep convolutional neural network.

The analysis of leukocyte recruitment in intravital video microscopy (IVM) is essential to the understanding of inflammatory processes. However, becau...

Combined virtual reality and haptic robotics induce space and movement invariant sensorimotor adaptation.

Prism adaptation is a method for studying visuomotor plasticity in healthy individuals, as well as for rehabilitating patients suffering spatial negle...

Using digital technologies in clinical trials: Current and future applications.

In 2015, we provided an overview of the use of digital technologies in clinical trials, both as a methodological tool and as a mechanism to deliver in...

Effect of Social Anxiety on the Adoption of Robotic Training Partner.

With the development of artificial intelligence technologies, robotic training partner is becoming a reality, which is a substitute for human training...

Adversarial symmetric GANs: Bridging adversarial samples and adversarial networks.

Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability. Despite many training stra...

Sleep-Dependent Memory Consolidation in a Neuromorphic Nanowire Network.

A neuromorphic network composed of silver nanowires coated with TiO is found to show certain parallels with neural networks in nature such as biologic...

Deep Learning in Proteomics.

Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively...

Acceleration Magnitude at Impact Following Loss of Balance Can Be Estimated Using Deep Learning Model.

Pre-impact fall detection can detect a fall before a body segment hits the ground. When it is integrated with a protective system, it can directly pre...

Associated Learning: Decomposing End-to-End Backpropagation Based on Autoencoders and Target Propagation.

Backpropagation (BP) is the cornerstone of today's deep learning algorithms, but it is inefficient partially because of backward locking, which means ...

Oxide-Based Electrolyte-Gated Transistors for Spatiotemporal Information Processing.

Spiking neural networks (SNNs) sharing large similarity with biological nervous systems are promising to process spatiotemporal information and can pr...

Predicting human health from biofluid-based metabolomics using machine learning.

Biofluid-based metabolomics has the potential to provide highly accurate, minimally invasive diagnostics. Metabolomics studies using mass spectrometry...

The delineation of largely deformed brain midline using regression-based line detection network.

PURPOSE: The human brain has two cerebral hemispheres that are roughly symmetric and separated by a midline, which is nearly a straight line shown in ...

SHIFT: speedy histological-to-immunofluorescent translation of a tumor signature enabled by deep learning.

Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it comp...

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks.

A basic-yet nontrivial-function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Stable neocorti...

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.

The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (MS)-based immunopeptideomics relies largely on dat...

Robot-assisted laparoscopic extravesical versus conventional laparoscopic extravesical ureteric reimplantation for pediatric primary vesicoureteric reflux: a systematic review and meta-analysis.

To perform a systematic review and meta-analysis comparing the outcomes of robotic-assisted laparoscopic extravesical ureteric reimplantation (RALUR) ...

Scheduling Sensor Duty Cycling Based on Event Detection Using Bi-Directional Long Short-Term Memory and Reinforcement Learning.

A smart home provides a facilitated environment for the detection of human activity with appropriate Deep Learning algorithms to manipulate data colle...

Identifying Heat Shock Protein Families from Imbalanced Data by Using Combined Features.

Heat shock proteins (HSPs) are ubiquitous in living organisms. HSPs are an essential component for cell growth and survival; the main function of HSPs...