Public Health

Development of artificial intelligence approach to forecasting oyster norovirus outbreaks along Gulf of Mexico coast.

This paper presents an artificial intelligence-based model, called ANN-2Day model, for forecasting, managing and ultimately eliminating the growing risk of oyster norovirus outbreaks. The ANN-2Day model was developed using Artificial Neural Network (ANN) Toolbox in MATLAB Program and 15-years of epidemiological and environmental data for six independent environmental predictors including water tem...

Evaluating Automatic Methods to Extract Patients' Supplement Use from Clinical Reports.

The widespread prevalence of dietary supplements has drawn extensive attention due to the safety and efficacy issue. Clinical notes document a great amount of detailed information on dietary supplement usage, thus providing a rich source for clinical research on supplement safety surveillance. Identification the use status of dietary supplements is one of the initial steps for the ultimate goal of...

Purification of influenza virus-like particles using sulfated cellulose membrane adsorbers.

BACKGROUND: Vaccines based on virus-like particles (VLPs) are an alternative to inactivated viral vaccines that combine good safety profiles with stro...

Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals...

Spatiotemporal Bayesian networks for malaria prediction.

Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models provid...

Critical dynamics in population vaccinating behavior.

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a c...

Lateral flow immunoassay and enzyme linked immunosorbent assay as effective immunomethods for the detection of synthetic cannabinoid JWH-200 based on the newly synthesized hapten.

In recent years, the use of synthetic cannabinoids (SCs) as drugs of abuse has greatly increased. SCs are associated with a risk of severe poisoning o...

Identification of recent cases of hepatitis C virus infection using physical-chemical properties of hypervariable region 1 and a radial basis function neural network classifier.

BACKGROUND: Identification of acute or recent hepatitis C virus (HCV) infections is important for detecting outbreaks and devising timely public healt...

Evaluation of fingerprinting techniques to assess genotype variation among Zygosaccharomyces strains.

Molecular typing techniques are key tools in surveillance of food spoilage yeasts, in investigations on intra-species population diversity, and in tra...

A systematic review of data mining and machine learning for air pollution epidemiology.

BACKGROUND: Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets o...

An ultrasensitive electrochemical immunosensor for Cry1Ab based on phage displayed peptides.

The rapid and widespread adoption of Bacillus thuringiensis (Bt) proteins in genetically modified (GM) crops has raised concerns about the impact of G...

An outbreak of classical swine fever in pigs in Bangladesh, 2015.

In a group of 22 healthy pigs aged between 4 and 6 months, 2 pigs became ill with high fever, complete anorexia, cough and abnormal swaying movements ...

A fuzzy MICMAC analysis for improving supply chain performance of basic vaccines in developing countries.

INTRODUCTION: In recent years, demand to improve child immunization coverage globally, and the development of the latest vaccines and technology has m...

Graph-based representation of behavior in detection and prediction of daily living activities.

Various surveillance systems capture signs of human activities of daily living (ADLs) and store multimodal information as time line behavioral records...

Determination of Tedizolid susceptibility interpretive criteria for gram-positive pathogens according to clinical and laboratory standards institute guidelines.

For effective antibacterial therapy, physicians require qualitative test results using susceptibility breakpoints provided by clinical microbiology la...

Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.

BACKGROUND: Automated disease code classification using free-text medical information is important for public health surveillance. However, traditiona...

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

BACKGROUND AND OBJECTIVE: T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine d...

Escape and surveillance asymmetries in locusts exposed to a Guinea fowl-mimicking robot predator.

Escape and surveillance responses to predators are lateralized in several vertebrate species. However, little is known on the laterality of escapes an...

Prediction of lung cancer patient survival via supervised machine learning classification techniques.

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance...

Survivability prediction of colon cancer patients using neural networks.

We utilize deep neural networks to develop prediction models for patient survival and conditional survival of colon cancer. Our models are trained and...