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Predicting post-stroke pneumonia using deep neural network approaches.

BACKGROUND AND PURPOSE: Pneumonia is a common complication after stroke, causing an increased length...

Post-hoc modification of linear models: Combining machine learning with domain information to make solid inferences from noisy data.

Linear machine learning models "learn" a data transformation by being exposed to examples of input w...

Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings.

Robots have the potential to help provide exercise therapy in a repeatable and reproducible manner f...

A two-stage deep learning approach for extracting entities and relationships from medical texts.

This work presents a two-stage deep learning system for Named Entity Recognition (NER) and Relation ...

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.

We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that i...

Post-processing radio-frequency signal based on deep learning method for ultrasonic microbubble imaging.

BACKGROUND: Improving imaging quality is a fundamental problem in ultrasound contrast agent imaging ...

CT Texture Analysis and Machine Learning Improve Post-ablation Prognostication in Patients with Adrenal Metastases: A Proof of Concept.

INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adre...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

BACKGROUND: The development of optimal classification criteria for specific mental disorders which s...

Metal artifact reduction for the segmentation of the intra cochlear anatomy in CT images of the ear with 3D-conditional GANs.

Cochlear implants (CIs) are surgically implanted neural prosthetic devices that are used to treat se...

Novel small molecule retrograde transport blocker confers post-exposure protection against ricin intoxication.

Ricin is a highly toxic type 2 ribosome-inactivating protein (RIP) which is extracted from the seeds...

Comparison of text processing methods in social media-based signal detection.

PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types...

Artificial Intelligence for Drug Toxicity and Safety.

Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, h...

Supplementation of OmniGen-AF improves the metabolic response to a glucose tolerance test in beef heifers.

This study determined whether feeding the immunomodulating supplement, OmniGen-AF, to feedlot heifer...

A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons.

It is known that brain can create a sparse representation of the environment in both sensory and mne...

Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback.

BACKGROUND: Add-on robot-mediated therapy has proven to be more effective than conventional therapy ...

Validation of computerized square-drawing based evaluation of motor function in patients with stroke.

Human-administered clinical scales are commonly used for quantifying motor performance and determini...

VesselNet: A deep convolutional neural network with multi pathways for robust hepatic vessel segmentation.

Extraction or segmentation of organ vessels is an important task for surgical planning and computer-...

Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer.

BACKGROUND: Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigila...

Effect of repetitive transcranial magnetic stimulation combined with robot-assisted training on wrist muscle activation post-stroke.

OBJECTIVE: To compare the effects of active assisted wrist extension training, using a robotic exosk...

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