Public Health & Policy

[Surveillance of Sensitivity to Penicillin in streptococcus Agalactiae recovered from pregnant women between 35-37 weeks of gestation].

Streptococcus agalactiae (GBS) cause severe infections in newborns under three months. Meningitis, pneumonia and sepsis are the main infectious diseases in these children. These infections are among the most serious that an individual can suffer in his first twelve hours of life. The child acquires the infection by vertical transmission of the colonized mother. To prevent neonatal disease, penicil...

Big Data in Public Health: Terminology, Machine Learning, and Privacy.

The digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores several key issues that have arisen around big data. First, we propose a taxonomy of sources of big data to clarify terminology and identify threads com...

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 ri...

E-Cigarette Surveillance With Social Media Data: Social Bots, Emerging Topics, and Trends.

BACKGROUND: As e-cigarette use rapidly increases in popularity, data from online social systems (Twitter, Instagram, Google Web Search) can be used to...

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 a...

Deep Gramulator: Improving Precision in the Classification of Personal Health-Experience Tweets with Deep Learning.

Health surveillance is an important task to track the happenings related to human health, and one of its areas is pharmacovigilance. Pharmacovigilance...

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...

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...

Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.

BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell ...

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 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 ...

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...

Propensity Scores in Pharmacoepidemiology: Beyond the Horizon.

PURPOSE OF REVIEW: Propensity score methods have become commonplace in pharmacoepidemiology over the past decade. Their adoption has confronted formid...

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...

A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults.

BACKGROUND: Type 2 diabetes is the most expensive chronic disease in the United States. Two-thirds of US adults have prediabetes or are overweight and...

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...