Public Health

SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.

Machine learning holds considerable promise for understanding complex biological processes such as v...

Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA.

Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant eco...

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutri...

Sentiment Analysis of Social Media on Childhood Vaccination: Development of an Ontology.

BACKGROUND: Although vaccination rates are above the threshold for herd immunity in South Korea, a g...

Ontology-based specification and generation of search queries for post-market surveillance.

BACKGROUND: The vigilant observation of medical devices during post-market surveillance (PMS) for id...

MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune...

Machine learning to refine decision making within a syndromic surveillance service.

BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situation...

Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.

BACKGROUND: Establishing epidemiological models and conducting predictions seems to be useful for th...

A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascula...

Endoscopic Surveillance of Barrett's Esophagus Using Volumetric Laser Endomicroscopy With Artificial Intelligence Image Enhancement.

Perceptions of drones, digital adherence monitoring technologies and educational videos for tuberculosis control in remote Madagascar: a mixed-method study protocol.

INTRODUCTION: Poor road and communication infrastructure pose major challenges to tuberculosis (TB) ...

Statistical learning approaches in the genetic epidemiology of complex diseases.

In this paper, we give an overview of methodological issues related to the use of statistical learni...

Likelihood-Based Methods for Assessing Principal Surrogate Endpoints in Vaccine Trials.

When evaluating principal surrogate biomarkers in vaccine trials, missingness in potential outcomes ...

Measuring social, environmental and health inequalities using deep learning and street imagery.

Cities are home to an increasing majority of the world's population. Currently, it is difficult to t...

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

OBJECTIVE: Local reactions are the most common vaccine-related adverse event. There is no specific d...

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, partic...

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

This study focuses on identifying environmental health risk factors related to acute respiratory dis...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form re...

Chief complaint classification with recurrent neural networks.

Syndromic surveillance detects and monitors individual and population health indicators through sour...

Drivers for the development of an Animal Health Surveillance Ontology (AHSO).

Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to ...

Automated detection of koalas using low-level aerial surveillance and machine learning.

Effective wildlife management relies on the accurate and precise detection of individual animals. Th...