Public Health & Policy

Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency virus prevention program based on offering pre-exposure prophylaxis (PrEP) to select high-risk individuals must balance the sensitivity of the binary c...

(matico) prevents collagen-induced platelet activation by decreasing phospholipase C-gamma 2 and protein kinase C phosphorylation signaling.

Platelets play a key role in thrombosis and cardiovascular diseases. Medicinal plants could be one of the most important factors that influence risks for platelet activation. (known as "matico") is a medicinal plant with many biological activities. The high content of polyphenols suggest that matico could have antiplatelet activity. The present study was aimed at evaluating mechanisms of antiplat...

Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction.

We sought to evaluate whether unbiased machine learning of dense phenotypic data ("phenomapping") could identify distinct hypertension subgroups that ...

A doubly robust approach for cost-effectiveness estimation from observational data.

Estimation of common cost-effectiveness measures, including the incremental cost-effectiveness ratio and the net monetary benefit, is complicated by t...

Identification of adverse drug-drug interactions through causal association rule discovery from spontaneous adverse event reports.

OBJECTIVE: Drug-drug interaction (DDI) is of serious concern, causing over 30% of all adverse drug reactions and resulting in significant morbidity an...

Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for th...

Metabolic changes in rat serum after administration of suberoylanilide hydroxamic acid and discriminated by SVM.

Suberoylanilide hydroxamic acid (SAHA) exerts marked anticancer effects via promotion of apoptosis, cell cycle arrest, and prevention of oncogene expr...

Twitter Influenza Surveillance: Quantifying Seasonal Misdiagnosis Patterns and their Impact on Surveillance Estimates.

BACKGROUND: Influenza (flu) surveillance using Twitter data can potentially save lives and increase efficiency by providing governments and healthcare...

Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston.

This paper continues an initiative conducted by the International Society for Disease Surveillance with funding from the Defense Threat Reduction Agen...

Prediction of lymph node parasite load from clinical data in dogs with leishmaniasis: An application of radial basis artificial neural networks.

Quantification of Leishmania infantum load via real-time quantitative polymerase chain reaction (qPCR) in lymph node aspirates is an accurate tool for...

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder.

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-y...

A genotypic method for determining HIV-2 coreceptor usage enables epidemiological studies and clinical decision support.

BACKGROUND: CCR5-coreceptor antagonists can be used for treating HIV-2 infected individuals. Before initiating treatment with coreceptor antagonists, ...

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nu...

Susceptibility Profiles of Isolates to Streptomycin and Rifampicin in Two Districts of the Eastern Region of Ghana.

. Drug resistance is a major challenge in antibiotic chemotherapy. Assessing resistance profiles of pathogens constitutes an essential surveillance to...

Efficacy of tildipirosin metaphylaxis for the prevention of respiratory disease, otitis and mortality in pre-weaned Holstein calves.

The aim of this study was to evaluate the efficacy of two metaphylactic approaches (long acting antibiotic injected once at 10 days of life or twice a...

Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of caus...

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid sym...

Social Media as a Sentinel for Disease Surveillance: What Does Sociodemographic Status Have to Do with It?

INTRODUCTION: Data from social media have been shown to have utility in augmenting traditional approaches to public health surveillance. Quantifying t...

Tackling Missing Data in Community Health Studies Using Additive LS-SVM Classifier.

Missing data is a common issue in community health and epidemiological studies. Direct removal of samples with missing data can lead to reduced sample...

An Intelligible Risk Stratification Model Based on Pairwise and Size Constrained Kmeans.

Having a system to stratify individuals according to risk is key to clinical disease prevention. This allows individuals identified at different risk ...