Work Force

Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data.

The study of complex microbial communities typically entails high-throughput sequencing and downstre...

Training a neural network for Gibbs and noise removal in diffusion MRI.

PURPOSE: To develop and evaluate a neural network-based method for Gibbs artifact and noise removal.

Robotics-assisted visual-motor training influences arm position sense in three-dimensional space.

BACKGROUND: Performing activities of daily living depends, among other factors, on awareness of the ...

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media.

BACKGROUND: High-quality medical resources are in high demand worldwide, and the application of arti...

Pair Potentials as Machine Learning Features.

Atom pairwise potential functions make up an essential part of many scoring functions for protein de...

Melanoma detection using adversarial training and deep transfer learning.

Skin lesion datasets consist predominantly of normal samples with only a small percentage of abnorma...

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.

The COVID-19 pandemia due to the SARS-CoV-2 coronavirus, in its first 4 months since its outbreak, h...

A Cancer Biologist's Primer on Machine Learning Applications in High-Dimensional Cytometry.

The application of machine learning and artificial intelligence to high-dimensional cytometry data s...

Systematic review with network meta-analysis of randomized controlled trials of robotic-assisted arm training for improving activities of daily living and upper limb function after stroke.

BACKGROUND: The aim of the present study was to to assess the relative effectiveness of the various ...

Machine learning prediction of combat basic training injury from 3D body shape images.

INTRODUCTION: Athletes and military personnel are both at risk of disabling injuries due to extreme ...

A Combined Deep-Learning and Lattice Boltzmann Model for Segmentation of the Hippocampus in MRI.

Segmentation of the hippocampus (HC) in magnetic resonance imaging (MRI) is an essential step for di...

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation.

Although having achieved great success in medical image segmentation, deep learning-based approaches...

Agents and robots for collaborating and supporting physicians in healthcare scenarios.

Monitoring patients through robotics telehealth systems is an interesting scenario where patients' c...

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences.

Engineering gene and protein sequences with defined functional properties is a major goal of synthet...

Disrupting clinical education: Using artificial intelligence to create training material.

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accel...

SpeckleGAN: a generative adversarial network with an adaptive speckle layer to augment limited training data for ultrasound image processing.

PURPOSE: In the field of medical image analysis, deep learning methods gained huge attention over th...

Utilizing artificial intelligence in endoscopy: a clinician's guide.

INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expe...

Gait Event Detection for Stroke Patients during Robot-Assisted Gait Training.

Functional electrical stimulation and robot-assisted gait training are techniques which are used in ...

Automated Recognition of Retinal Pigment Epithelium Cells on Limited Training Samples Using Neural Networks.

PURPOSE: To develop a neural network (NN)-based approach, with limited training resources, that iden...

Age-Related Differences in the Uncanny Valley Effect.

BACKGROUND: Due to declining birthrates and an increasing aging population, shortage of the caregivi...