Allergy

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.

BACKGROUND: The ability to confidently predict health outcomes from gene expression would catalyze a...

A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds...

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

PURPOSE: Tumor genomic features have been of particular interest because of their potential impact o...

A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. R...

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consen...

Vitamin D and Serum Immunoglobulin E Levels in Allergic Rhinitis: A Case-control Study from Pakistan.

Introduction Allergic rhinitis (AR) is the most common non-infectious rhinitis and is associated wit...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The wide adoption of electronic health record systems in health care generates big real-world data t...

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex...

Identification of Catecholamine Neurotransmitters Using a Fluorescent Electronic Tongue.

Catecholamine neurotransmitters, specifically, dopamine (DA), epinephrine (EP), and norepinephrine (...

In vitro selection of DNA aptamers and their integration in a competitive voltammetric biosensor for azlocillin determination in waste water.

The uncontrolled usage of veterinary antibiotics has led to their widespread pollution in waterways ...

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks.

The importance of T cells in immunotherapy has motivated developing technologies to improve therapeu...

Efficient expression of EpEX in the cytoplasm of using thioredoxin fusion protein.

Recombinant epithelial cell adhesion molecule extracellular domain (EpEX) has a high potential as a ...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vacc...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the...

Deep learning for pollen allergy surveillance from twitter in Australia.

BACKGROUND: The paper introduces a deep learning-based approach for real-time detection and insights...

Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry.

Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information-rich images of singl...

White blood cells detection and classification based on regional convolutional neural networks.

White blood cells (WBC) are important parts of our immune system and they protect our body against i...

DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity.

Neoantigens play important roles in cancer immunotherapy. Current methods used for neoantigen predic...

DeepTetrad: high-throughput image analysis of meiotic tetrads by deep learning in Arabidopsis thaliana.

Meiotic crossovers facilitate chromosome segregation and create new combinations of alleles in gamet...

Dietary reference values for sodium.

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food ...

Identifying Phenotypes of Atopic Dermatitis in a Longitudinal United States Cohort Using Unbiased Statistical Clustering.