Practice Management

Medication Adherence and Stroke Prevention: What Real World Data Tells Us.

Medication adherence, by definition,(2) is "the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen." Poor medication adherence can interfere with the ability to treat many diseases, leading to greater complications and a lower quality of life.(3) In this issue of Acta Neurologica Taiwanica, Chen et al.(4) presented the inverse association between...

Functional interpretation of genetic variants using deep learning predicts impact on chromatin accessibility and histone modification.

Identifying functional variants underlying disease risk and adoption of personalized medicine are currently limited by the challenge of interpreting the functional consequences of genetic variants. Predicting the functional effects of disease-associated protein-coding variants is increasingly routine. Yet, the vast majority of risk variants are non-coding, and predicting the functional consequence...

High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.

OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the a...

Coding and classifying GP data: the POLAR project.

BACKGROUND: Data, particularly 'big' data are increasingly being used for research in health. Using data from electronic medical records optimally req...

Integration of Anatomy Ontologies and Evo-Devo Using Structured Markov Models Suggests a New Framework for Modeling Discrete Phenotypic Traits.

Modeling discrete phenotypic traits for either ancestral character state reconstruction or morphology-based phylogenetic inference suffers from ambigu...

The promises and perils of automated facial action coding in studying children's emotions.

Computer vision algorithms have made tremendous advances in recent years. We now have algorithms that can detect and recognize objects, faces, and eve...

TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.

Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex phenotypes. Most human SNPs fall in non-coding regi...

Teaching Digital, Block-Based Coding of Robots to High School Students with Autism Spectrum Disorder and Challenging Behavior.

The use of robots to teach students with autism spectrum disorder communication skills has basis in the literature; however, research investigating th...

Uncovering the mouse olfactory long non-coding transcriptome with a novel machine-learning model.

Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in ol...

DeepCNPP: Deep Learning Architecture to Distinguish the Promoter of Human Long Non-Coding RNA Genes and Protein-Coding Genes.

Promoter region of protein-coding genes are gradually being well understood, yet no comparable studies exist for the promoter of long non-coding RNA (...

A Machine-Learning Algorithm to Optimise Automated Adverse Drug Reaction Detection from Clinical Coding.

INTRODUCTION: Adverse drug reaction (ADR) detection in hospitals is heavily reliant on spontaneous reporting by clinical staff, with studies in the li...

Teaching Robotics Coding to a Student with ASD and Severe Problem Behavior.

Research on teaching STEM, especially in the areas of teaching coding for students with ASD, is lacking. The purpose of the current study was to evalu...

[Prediction of protein subcellular localization based on multilayer sparse coding].

In order to provide a theoretical basis for better understanding the function and properties of proteins, we proposed a simple and effective feature e...

Integrating an Ontology of Radiology Differential Diagnosis with ICD-10-CM, RadLex, and SNOMED CT.

An ontology offers a human-readable and machine-computable representation of the concepts in a domain and the relationships among them. Mappings betwe...

[Effects of long non-coding RNA RP1-90L14.1 on the biological behaviors of cancer prostate LNCaP cells and its regulating mechanisms].

OBJECTIVE: To investigate the effects of long non-coding RNA RP1-90L14.1 on the proliferation, migration and invasion of prostate cancer LNCaP cells a...

Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning.

AIMS: Electrical storm (ES) is a serious arrhythmic syndrome that is characterized by recurrent episodes of ventricular arrhythmias. Electrical storm ...

Linking Health Records with Knowledge Sources Using OWL and RDF.

This paper describes a method by which the Web Ontology Language (OWL) can be used to specify a highly structured health record, following internation...

DNA Steganalysis Using Deep Recurrent Neural Networks.

Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in stega...

Comparison of Natural Language Processing and Manual Coding for the Identification of Cross-Sectional Imaging Reports Suspicious for Lung Cancer.

PURPOSE: To compare the accuracy and reliability of a natural language processing (NLP) algorithm with manual coding by radiologists, and the combinat...

LncRNAnet: long non-coding RNA identification using deep learning.

MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes. LncRNAs share similar sequence characteristics w...