Practice Management

Latest AI and machine learning research in practice management for healthcare professionals.

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Coding and classifying GP data: the POLAR project.

BACKGROUND: Data, particularly 'big' data are increasingly being used for research in health. Using ...

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

OBJECTIVE: Electronic health records linked with biorepositories are a powerful platform for transla...

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 tha...

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 morpholog...

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 p...

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 epithel...

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 ...

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 studi...

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 lack...

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 r...

[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 prot...

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 domai...

Developing Machine Learning Models for Behavioral Coding.

OBJECTIVE: The goal of this research is to develop a machine learning supervised classification mode...

[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, migra...

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 epis...

DNA Steganalysis Using Deep Recurrent Neural Networks.

Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucl...

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 high...

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 wi...

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

MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

The current deluge of newly identified RNA transcripts presents a singular opportunity for improved ...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of...

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