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Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.

The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely obese have shown minimal complication, long-term outcomes are understudied. Previously, we reported no difference in 6-month patient and graft survival among 28 robot-assisted transplant cases (2009-2013) and 28 open controls (2004-2010). Groups were f...

Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiology when analysed in detail can however be predictive of acute deterioration leading to cardiac or respiratory arrests. This paper seeks to exploit the ...

Robotic Assessment of Motor, Sensory, and Cognitive Function in Acute Sport-Related Concussion and Recovery.

There is a need for better tools to objectively, reliably, and precisely assess neurological function after sport-related concussion (SRC). The aim of...

Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning.

The risk stratification of prostate cancer and breast cancer tumours from patients relies on histopathology, selective genomic testing, or on other me...

Experimental infection of Friesian bulls with Theileria orientalis (Ikeda) and effects on the haematocrit, live weight, rectal temperature and activity.

Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis (Ikeda), an obligate intracellular pr...

Segmenting the Brain Surface From CT Images With Artifacts Using Locally Oriented Appearance and Dictionary Learning.

The accurate segmentation of the brain surface in post-surgical computed tomography (CT) images is critical for image-guided neurosurgical procedures ...

Mining heterogeneous networks with topological features constructed from patient-contributed content for pharmacovigilance.

Drug safety, also called pharmacovigilance, represents a serious health problem all over the world. Adverse drug reactions (ADRs) and drug-drug intera...

Normalizing Spontaneous Reports Into MedDRA: Some Experiments With MagiCoder.

Text normalization into medical dictionaries is useful to support clinical tasks. A typical setting is pharmacovigilance (PV). The manual detection of...

Shared spatiotemporal category representations in biological and artificial deep neural networks.

Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elu...

Using natural language processing methods to classify use status of dietary supplements in clinical notes.

BACKGROUND: Despite widespread use, the safety of dietary supplements is open to doubt due to the fact that they can interact with prescribed medicati...

Chemical-induced disease extraction via recurrent piecewise convolutional neural networks.

BACKGROUND: Extracting relationships between chemicals and diseases from unstructured literature have attracted plenty of attention since the relation...

iMethyl-STTNC: Identification of N-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences.

N- methyladenosine (mA) is a vital post-transcriptional modification, which adds another layer of epigenetic regulation at RNA level. It chemically mo...

The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Despite upper extremity function playing a crucial role in maintaining one's independence in activities of daily living, upper extremity impairments r...

Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction.

BACKGROUND: Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-hea...

Intuitive Assessment of Mortality Based on Facial Characteristics: Behavioral, Electrocortical, and Machine Learning Analyses.

Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objec...

Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients.

To assess functional status and robot-based kinematic measures four years after subacute robot-assisted rehabilitation in hemiparesis. Twenty-two pa...

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extrac...

Towards precision informatics of pharmacovigilance: OAE-CTCAE mapping and OAE-based representation and analysis of adverse events in patients treated with cancer drugs.

A critical issue in the usage of cancer drugs is its association with various adverse events (AEs) in some, but not all, patients. The National Cancer...

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus a...

Fully automatic detection and segmentation of abdominal aortic thrombus in post-operative CTA images using Deep Convolutional Neural Networks.

Computerized Tomography Angiography (CTA) based follow-up of Abdominal Aortic Aneurysms (AAA) treated with Endovascular Aneurysm Repair (EVAR) is esse...