Public Health

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 system to destroy cancer cells expressing unique peptide signatures (neoepitopes). Administrations of cancer-specific neoepitopes in the form of synthetic peptide vaccine have been proven effective in both mouse models and human patients. Because only a tiny fraction of cancer-specific neoepitopes ...

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 the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the periodic variations in time series. However, these models cannot handle the nonlinear trends correctly. Recurrent neural networks can address problems that ...

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

BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public he...

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 cardiovascular risk. This study aims at predicting, with a cert...

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) control in many regions of the world. TB surveilla...

Measurement of physical activity in clinical practice using accelerometers.

Accelerometers are commonly used in clinical and epidemiological research for more detailed measures of physical activity and to target the limitation...

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, particularly elderly people, are at some degree of risk ...

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 diseases using deep learning method. Based on respira...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form requires monitoring and repeat serological and molec...

Chief complaint classification with recurrent neural networks.

Syndromic surveillance detects and monitors individual and population health indicators through sources such as emergency department records. Automate...

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

Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems whe...

Lung Cancer Survival Prediction via Machine Learning Regression, Classification, and Statistical Techniques.

A regression model is developed to predict survival time in months for lung cancer patients. It was previously shown that predictive models perform ac...

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity.

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules induces the prolongation of the QT interval which leads to fatal ca...

Artificial Neural Network for in-Bed Posture Classification Using Bed-Sheet Pressure Sensors.

Pressure ulcer prevention is a vital procedure for patients undergoing long-term hospitalization. A human body lying posture (HBLP) monitoring system ...

Statistical outbreak detection by joining medical records and pathogen similarity.

We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines p...

Semi-supervised learning to improve generalizability of risk prediction models.

The utility of a prediction model depends on its generalizability to patients drawn from different but related populations. We explored whether a semi...

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal .

Nontyphoidal species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susce...

Gallic Acid Potentiates the Antimicrobial Activity of Tulathromycin Against Two Key Bovine Respiratory Disease (BRD) Causing-Pathogens.

Bovine respiratory disease (BRD) is the most common infectious disease in dairy and beef cattle. It is associated with significant morbidity and morta...

The Immunogenicity of the C Fragment of Tetanus Neurotoxin in Production of Tetanus Antitoxin.

The demand of tetanus antitoxin (TAT) as tetanus treatment in developing and underdeveloped countries is still great since it is relatively easy to ac...

Postmarketing surveillance on clinical use of edoxaban in patients with nonvalvular atrial fibrillation (ETNA-AF-Japan): Three-month interim analysis results.

BACKGROUND: Direct oral anticoagulants are the first-line drugs for anticoagulation therapy in nonvalvular atrial fibrillation (NVAF). However, a real...