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Capsule network for protein post-translational modification site prediction.

MOTIVATION: Computational methods for protein post-translational modification (PTM) site prediction ...

Prediction of Personal Experience Tweets of Medication Use via Contextual Word Representations.

Continuous monitoring the safe use of medication is an important task in pharmacovigilance. The firs...

Soft Robotic Bilateral Hand Rehabilitation System for Fine Motor Learning.

This paper presents the development of a pneumatically actuated soft robotic based bilateral therapy...

Assessment of human wrist rigidity and pain in post-traumatic patients.

The aim of this work is to present a novel robot-based method to assess the sources of a lack of fun...

Comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

We appreciate the detailed review provided by Magge et al1 of our article, "Deep learning for pharma...

Re: Minimally Invasive, Robot-Assisted Procedure for Kidney Transplantation among Morbidly Obese: Positive Outcomes at 5 Years Post-Transplant.

Differentiating post-cancer from healthy tongue muscle coordination patterns during speech using deep learning.

The ability to differentiate post-cancer from healthy tongue muscle coordination patterns is necessa...

Artificial Intelligence Within Pharmacovigilance: A Means to Identify Cognitive Services and the Framework for Their Validation.

INTRODUCTION: Pharmacovigilance (PV) detects, assesses, and prevents adverse events (AEs) and other ...

Re: Removing the Urinary Catheter on Post-Operative Day 2 after Robot-Assisted Laparoscopic Radical Prostatectomy: A Feasibility Study from a Single High-Volume Referral Centre.

Artificial Intelligence and the Future of the Drug Safety Professional.

The healthcare industry, and specifically the pharmacovigilance industry, recognizes the need to sup...

gazeNet: End-to-end eye-movement event detection with deep neural networks.

Existing event detection algorithms for eye-movement data almost exclusively rely on thresholding on...

Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks.

BACKGROUND AND SIGNIFICANCE: Adverse drug events (ADEs) occur in approximately 2-5% of hospitalized ...

Adverse Drug Event Detection from Electronic Health Records Using Hierarchical Recurrent Neural Networks with Dual-Level Embedding.

INTRODUCTION: Adverse drug event (ADE) detection is a vital step towards effective pharmacovigilance...

MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes.

INTRODUCTION: Early detection of adverse drug events (ADEs) from electronic health records is an imp...

Efficacy, chondrotoxicity and plasma concentrations of tramadol following intra-articular administration in horses undergoing arthroscopy: preliminary findings.

Intra-articular administration of analgesics is performed to ensure good perioperative pain manageme...

Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning.

OBJECTIVEFlow diverters (FDs) are designed to occlude intracranial aneurysms (IAs) while preserving ...

A chronological pharmacovigilance network analytics approach for predicting adverse drug events.

OBJECTIVES: This study extends prior research by combining a chronological pharmacovigilance network...

Effectiveness of a single session of dual-transcranial direct current stimulation in combination with upper limb robotic-assisted rehabilitation in chronic stroke patients: a randomized, double-blind, cross-over study.

The impact of transcranial direct current stimulation (tDCS) is controversial in the neurorehabilita...

Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions.

Impedimetric biosensors for measuring small molecules based on weak/transient interactions between b...

Drug-drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths.

MOTIVATION: Adverse events resulting from drug-drug interactions (DDI) pose a serious health issue. ...