AI Medical Compendium Topic

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Disease Outbreaks

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Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

BMJ open
OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections ...

The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing.

Computational intelligence and neuroscience
Ebola virus disease (EVD) distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, ...

Quantifying the determinants of outbreak detection performance through simulation and machine learning.

Journal of biomedical informatics
OBJECTIVE: To develop a probabilistic model for discovering and quantifying determinants of outbreak detection and to use the model to predict detection performance for new outbreaks.

Global Epidemiology of Outbreaks of Unknown Cause Identified by Open-Source Intelligence, 2020-2022.

Emerging infectious diseases
Epidemic surveillance using traditional approaches is dependent on case ascertainment and is delayed. Open-source intelligence (OSINT)-based syndromic surveillance can overcome limitations of delayed surveillance and poor case ascertainment, providin...

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Molecular biology and evolution
Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancements, including the application of deep learning to overcome computational limitations, significant cha...

Automated cooling tower detection through deep learning for Legionnaires' disease outbreak investigations: a model development and validation study.

The Lancet. Digital health
BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be pr...

Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases.

Mathematical biosciences and engineering : MBE
COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since the pandemic outbreak in 2019. Predicting infectious disease outbreaks is crucial for effective prevention and control....

Predicting malaria outbreaks using earth observation measurements and spatiotemporal deep learning modelling: a South Asian case study from 2000 to 2017.

The Lancet. Planetary health
BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogene...

AI-based epidemic and pandemic early warning systems: A systematic scoping review.

Health informatics journal
Timely detection of disease outbreaks is critical in public health. Artificial Intelligence (AI) can identify patterns in data that signal the onset of epidemics and pandemics. This scoping review examines the effectiveness of AI in epidemic and pan...