AI Medical Compendium Topic

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Disease Outbreaks

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Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study.

JMIR public health and surveillance
BACKGROUND: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to ...

Prediction of the Vaccine-derived Poliovirus Outbreak Incidence: A Hybrid Machine Learning Approach.

Scientific reports
Recently, significant attention has been devoted to vaccine-derived poliovirus (VDPV) surveillance due to its severe consequences. Prediction of the outbreak incidence of VDPF requires an accurate analysis of the alarming data. The overarching aim to...

AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data.

Journal of medical systems
The novel coronavirus (COVID-19) outbreak, which was identified in late 2019, requires special attention because of its future epidemics and possible global threats. Beside clinical procedures and treatments, since Artificial Intelligence (AI) promis...

Feature selection based multivariate time series forecasting: An application to antibiotic resistance outbreaks prediction.

Artificial intelligence in medicine
Antimicrobial resistance has become one of the most important health problems and global action plans have been proposed globally. Prevention plays a key role in these actions plan and, in this context, we propose the use of Artificial Intelligence, ...

Integration of shared-pathogen networks and machine learning reveals the key aspects of zoonoses and predicts mammalian reservoirs.

Proceedings. Biological sciences
Diseases that spread to humans from animals, zoonoses, pose major threats to human health. Identifying animal reservoirs of zoonoses and predicting future outbreaks are increasingly important to human health and well-being and economic stability, par...

Forecast of Dengue Cases in 20 Chinese Cities Based on the Deep Learning Method.

International journal of environmental research and public health
Dengue fever (DF) is one of the most rapidly spreading diseases in the world, and accurate forecasts of dengue in a timely manner might help local government implement effective control measures. To obtain the accurate forecasting of DF cases, it is ...

Location of sources in reaction-diffusion equations using support vector machines.

PloS one
The reaction-diffusion equation serves to model systems in the diffusion regime with sources. Specific applications include diffusion processes in chemical reactions, as well as the propagation of species, diseases, and populations in general. In som...

Attention-based recurrent neural network for influenza epidemic prediction.

BMC bioinformatics
BACKGROUND: Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat to the society, precise real-time forecasting of influenza outbreaks is of great value to our public.

Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning.

Geospatial health
Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is endemic. A vaccine is not available and has yet to reach the market due to the economic burden of d...

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Preventive veterinary medicine
Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respiratory syndrome virus (PRRSv). The assessment of biosecurity practices in breeding herds is usually don...