AIMC Topic: Epidemics

Clear Filters Showing 31 to 40 of 51 articles

A dynamic neural network model for predicting risk of Zika in real time.

BMC medicine
BACKGROUND: In 2015, the Zika virus spread from Brazil throughout the Americas, posing an unprecedented challenge to the public health community. During the epidemic, international public health officials lacked reliable predictions of the outbreak's...

Novel epidemic models on PSO-based networks.

Journal of theoretical biology
This paper proposes two spatio-temporal epidemic network models based on popularity and similarity optimization (PSO), called r-SI and r-SIS, respectively, in which new connections take both popularity and similarity into account. In the spatial dime...

Development and evaluation of a deep learning approach for modeling seasonality and trends in hand-foot-mouth disease incidence in mainland China.

Scientific reports
The high incidence, seasonal pattern and frequent outbreaks of hand, foot, and mouth disease (HFMD) represent a threat for millions of children in mainland China. And advanced response is being used to address this. Here, we aimed to model time serie...

Weekly ILI patient ratio change prediction using news articles with support vector machine.

BMC bioinformatics
BACKGROUND: Influenza continues to pose a serious threat to human health worldwide. For this reason, detecting influenza infection patterns is critical. However, as the epidemic spread of influenza occurs sporadically and rapidly, it is not easy to e...

Artificial Intelligence Transforms the Future of Health Care.

The American journal of medicine
Life sciences researchers using artificial intelligence (AI) are under pressure to innovate faster than ever. Large, multilevel, and integrated data sets offer the promise of unlocking novel insights and accelerating breakthroughs. Although more data...

Estimation of the Basic Reproduction Number and Vaccination Coverage of Influenza in the United States (2017-18).

Journal of research in health sciences
BACKGROUND: Determining the epidemic threshold parameter helps health providers calculate the coverage while guiding them in planning the process of vaccination strategy. Since the trend and mechanism of influenza is very similar in different countri...

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

PloS one
BACKGROUND: AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the 'big data' aggregated from Internet search engines, which contain users' information on the ...

The Apollo Structured Vocabulary: an OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation.

Journal of biomedical semantics
BACKGROUND: We developed the Apollo Structured Vocabulary (Apollo-SV)-an OWL2 ontology of phenomena in infectious disease epidemiology and population biology-as part of a project whose goal is to increase the use of epidemic simulators in public heal...

Epidemics in interconnected small-world networks.

PloS one
Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-wor...

Practical Approach for Evaluating Machine Learning Anomaly Detection Algorithms for Epidemic Early Warning Systems.

Studies in health technology and informatics
Anomaly detection methods in time series data can play a pivotal role in epidemic surveillance Early Warning Systems (EWS). Statistical and rules-based methods have been traditionally employed in such systems, but are challenged by data dynamics and ...