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Disease Outbreaks

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

Epidemics
Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant economic and public health impacts necessitate development of accurate and efficient algorithms for forecasting of any upcoming influenza outbreaks. Most...

Regional level influenza study based on Twitter and machine learning method.

PloS one
The significance of flu prediction is that the appropriate preventive and control measures can be taken by relevant departments after assessing predicted data; thus, morbidity and mortality can be reduced. In this paper, three flu prediction models, ...

Booster immunity - diagnosis of chronic hepatitis B viral infection.

Journal of infection in developing countries
INTRODUCTION: Diagnosis of chronic hepatitis B virus (HBV) infection particularly its occult form requires monitoring and repeat serological and molecular studies. The aim of the study was to investigate the possible relation between the case of a fa...

Statistical outbreak detection by joining medical records and pathogen similarity.

Journal of biomedical informatics
We present a statistical inference model for the detection and characterization of outbreaks of hospital associated infection. The approach combines patient exposures, determined from electronic medical records, and pathogen similarity, determined by...

Kyasanur Forest Disease Classification Framework Using Novel Extremal Optimization Tuned Neural Network in Fog Computing Environment.

Journal of medical systems
Kyasanur Forest Disease (KFD) is a life-threatening tick-borne viral infectious disease endemic to South Asia and has been taking so many lives every year in the past decade. But recently, this disease has been witnessed in other regions to a large e...

Deep learning for supervised classification of spatial epidemics.

Spatial and spatio-temporal epidemiology
In an emerging epidemic, public health officials must move quickly to contain the spread. Information obtained from statistical disease transmission models often informs the development of containment strategies. Inference procedures such as Bayesian...

Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models.

Journal of medical Internet research
BACKGROUND: Timely understanding of public perceptions allows public health agencies to provide up-to-date responses to health crises such as infectious diseases outbreaks. Social media such as Twitter provide an unprecedented way for the prompt asse...

Mapping the transmission risk of Zika virus using machine learning models.

Acta tropica
Zika virus, which has been linked to severe congenital abnormalities, is exacerbating global public health problems with its rapid transnational expansion fueled by increased global travel and trade. Suitability mapping of the transmission risk of Zi...

Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social media are important platforms for risk communication during public health crises. Effective dissemination of accurate, relevant, and up-to-date health information is important for the public to raise awareness and develop risk management strat...

Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network.

Scientific reports
Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may help save lives. In this paper, we use the Twitter data set and the United States Centers for Disea...