AIMC Topic: Communicable Disease Control

Clear Filters Showing 21 to 30 of 46 articles

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.

BioMed research international
The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel f...

Event-Driven Deep Learning for Edge Intelligence (EDL-EI).

Sensors (Basel, Switzerland)
Edge intelligence (EI) has received a lot of interest because it can reduce latency, increase efficiency, and preserve privacy. More significantly, as the Internet of Things (IoT) has proliferated, billions of portable and embedded devices have been ...

Deep learning of contagion dynamics on complex networks.

Nature communications
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically or computationally tractable, these models must rely on simplifying assumptions, thereby limiti...

The Infectious Disease Ontology in the age of COVID-19.

Journal of biomedical semantics
BACKGROUND: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially f...

A fusion of data science and feed-forward neural network-based modelling of COVID-19 outbreak forecasting in IRAQ.

Journal of biomedical informatics
BACKGROUND: Iraq is among the countries affected by the COVID-19 pandemic. As of 2 August 2020, 129,151 COVID-19 cases were confirmed, including 91,949 recovered cases and 4,867 deaths. After the announcement of lockdown in early April 2020, situatio...

Trends in reasons for emergency calls during the COVID-19 crisis in the department of Gironde, France using artificial neural network for natural language classification.

Scandinavian journal of trauma, resuscitation and emergency medicine
OBJECTIVES: During periods such as the COVID-19 crisis, there is a need for responsive public health surveillance indicators in order to monitor both the epidemic growth and potential public health consequences of preventative measures such as lockdo...

AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19.

Scientific data
The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease, governments worldwide have implemented non-pharmaceutical interventio...

A Knowledge-Based Algorithm for Automatic Monitoring of Orthodontic Treatment: The Dental Monitoring System. Two Cases.

Sensors (Basel, Switzerland)
BACKGROUND: In the dental field, digital technology has created new opportunities for orthodontists to integrate their clinical practice, and for patients to collect information about orthodontics and their treatment, which is called "teledentistry."...

Machine learning techniques to detect and forecast the daily total COVID-19 infected and deaths cases under different lockdown types.

Microscopy research and technique
COVID-19 has impacted the world in many ways, including loss of lives, economic downturn and social isolation. COVID-19 was emerged due to the SARS-CoV-2 that is highly infectious pandemic. Every country tried to control the COVID-19 spread by imposi...

A comparison of the value of two machine learning predictive models to support bovine tuberculosis disease control in England.

Preventive veterinary medicine
Nearly a decade into Defra's current eradication strategy, bovine tuberculosis (bTB) remains a serious animal health problem in England, with c.30,000 cattle slaughtered annually in the fight against this insidious disease. There is an urgent need to...