Related papers: Innovative in silico approaches to address avian f…
The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the Internet.…
The global spread of avian influenza A viruses in domestic birds is causing dramatic economic and social losses. Various mechanistic models have been developed in an attempt to better understand avian influenza transmission and to evaluate…
One Health issues, such as the spread of highly pathogenic avian influenza~(HPAI), present significant challenges at the human-animal-environmental interface. Recent H5N1 outbreaks underscore the need for comprehensive modeling efforts that…
In this work, we present an approach called Disease Informed Neural Networks (DINNs) that can be employed to effectively predict the spread of infectious diseases. This approach builds on a successful physics informed neural network…
Recent development in unmanned UAV technology paved the way for numerous applications in diverse cross discipline fields. One of the main feature of UAV s are their portability in terms of size that allows them to navigate through fairly…
Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While…
A method for detecting a trend change in cross-border epidemic transmission is developed for a standard epidemiological SIR compartment model and a meta-population network model. The method is applicable to investigating the efficacy of the…
The storage and manipulation of digital images and the analysis of the information held in those images are essential requirements for next-generation medical information systems. The medical community has been exploring collaborative…
The recognition of the importance of drug-like properties beyond potency to reduce clinical attrition of biologics has driven significant progress in the development of in vitro and in silico tools for developability assessment of antibody…
We present a study of the worldwide spread of a pandemic influenza and its possible containment at a global level taking into account all available information on air travel. We studied a metapopulation stochastic epidemic model on a global…
The availability of empirical data that capture the structure and behavior of complex networked systems has been greatly increased in recent years, however a versatile computational toolbox for unveiling a complex system's nodal and…
The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies.…
Infectious diseases on farms pose both public and animal health risks, so understanding how they spread between farms is crucial for developing disease control strategies to prevent future outbreaks. We develop novel Bayesian nonparametric…
This paper presents a perspective on the Healthgrid initiative which involves European projects deploying pioneering applications of grid technology in the health sector. In the last couple of years, several grid projects have been funded…
The pandemic caused by SARS-CoV-2 has left an unprecedented impact on health, economy and society worldwide. Emerging strains are making pandemic management increasingly challenging. There is an urge to collect epidemiological, clinical,…
To support the ongoing management of viral respiratory diseases, many countries are moving towards an integrated model of surveillance for SARS-CoV-2, influenza, and other respiratory pathogens. While many surveillance approaches catalysed…
The evolution of the hemagglutinin amino acids sequences of Influenza A virus is studied by a method based on an informational metrics, originally introduced by Rohlin for partitions in abstract probability spaces. This metrics does not…
Disease spreading through human travel networks has been a topic of great interest in recent years, as witnessed during outbreaks of influenza A (H1N1) or SARS pandemics. One way to stop spreading over the airline network are travel…
This study presents a novel approach at the intersection of genomic analysis and artificial intelligence (AI) to predict viral mutations and assess the risks of future pandemics. Through comprehensive genomic analysis, genetic markers…
Many biological networks have to filter out useful information from a vast excess of spurious interactions. We use computational evolution to predict design features of networks processing ligand categorization. The important problem of…