Prescriptions

Neural activity reveals interactions between episodic and semantic memory systems during retrieval.

Whereas numerous findings support a distinction between episodic and semantic memory, it is now widely acknowledged that these two forms of memory interact during both encoding and retrieval. The precise nature of this interaction, however, remains poorly understood. To examine the role of semantic organization during episodic encoding and retrieval, we recorded intracranial encephalographic signa...

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 important, challenging task to support pharmacovigilance and drug safety surveillance. A well-known challenge to use clinical text for detection of ADEs is that much of the detailed information is documented in a narrative manner. Clinical natural language processing (NLP) is the key technology to extr...

Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

INTRODUCTION: This work describes the Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) corpus and provides an overview of ...

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 and prevention of future incidents caused by pote...

Detecting Adverse Drug Events with Rapidly Trained Classification Models.

INTRODUCTION: Identifying occurrences of medication side effects and adverse drug events (ADEs) is an important and challenging task because they are ...

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 patients, often resulting in poor outcomes or even...

Evaluating the diameter of eyedropper tips using a computer vision system.

PURPOSE: This study aimed to determine the variation in diameters of outer and inner apertures of eyedropper tips using a computer vision system. Stan...

Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning.

The creation of big clinical data cohorts for machine learning and data analysis require a number of steps from the beginning to successful completion...

Evaluation of Chatbot Prototypes for Taking the Virtual Patient's History.

In medical education Virtual Patients (VP) are often applied to train students in different scenarios such as recording the patient's medical history ...

Current status and future perspective of computational toxicology in drug safety assessment under ontological intellection.

For the safety assessment of pharmaceuticals, initial data management requires accurate toxicological data acquisition, which is based on regulatory s...

Regeneration of Denervated Skeletal Muscles - Brunelli's CNS-PNS Paradigm.

The restoration of voluntary muscle activity in posttraumatic paraplegia in both animal experiments and other clinical applications requires reproduci...

The 18th FRAME Annual Lecture, October 2019: Human Trials in Pharmacology.

Safety and efficacy testing is a crucial part of the drug development process, and several different methods are used to obtain the necessary data (e....

Effects of Baneh () Gum on Human Breast Cancer Cell Line (MCF-7) and Its Interaction with Anticancer Drug Doxorubicin.

is one of the species of that grows in the wild in different regions of Iran. Traditionally, family has antibacterial, fungicidal, and cytotoxic pr...

Effectiveness of robot-assisted gait training on motor impairments in people with Parkinson's disease: a systematic review and meta-analysis.

The aim of this systematic review and meta-analysis was to evaluate the effectiveness of robot-assisted gait training (RAGT) on motor impairments in p...

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 management avoiding undesirable systemic effects. To evalu...

Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications.

OBJECTIVE: The aim of this work is to leverage relational information extracted from biomedical literature using a novel synthesis of unsupervised pre...

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

OBJECTIVES: This study extends prior research by combining a chronological pharmacovigilance network approach with machine-learning (ML) techniques to...

Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks.

Classification of plants based on a multi-organ approach is very challenging. Although additional data provide more information that might help to dis...

Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed.

BACKGROUND: Host-parasite protein interactions (HPPI) are those interactions occurring between a parasite and its host. Host-parasite protein interact...

Modeling polypharmacy side effects with graph convolutional networks.

MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a...