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A novel coronavirus disease has emerged (later named COVID-19) and caused the world to enter a new reality, with many direct and indirect factors influencing it. Some are human-controllable (e.g. interventional policies, mobility and the…
More than ever COVID-19 is putting pressure on health systems all around the world, especially in Brazil. In this study we propose an analytical approach based on statistics and machine learning that uses lab exam data coming from patients…
Data assimilation is used to optimally fit a classical epidemiology model to the Johns Hopkins data of the Covid-19 pandemic. The optimisation is based on the confirmed cases and confirmed deaths. This is the only data available with…
Cybersecurity decision-making increasingly occurs in environments characterized by uncertainty, partial observability, and adversarial manipulation, where heterogeneous signals from multiple sources are often incomplete, ambiguous, or…
This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence, namely psychology and engineering, and from disciplines aiming to regulate AI innovations, namely AI…
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…
The COVID-19 outbreak was announced as a global pandemic by the World Health Organisation in March 2020 and has affected a growing number of people in the past few weeks. In this context, advanced artificial intelligence techniques are…
This review explores the integration of Artificial Intelligence into Horizon Scanning, focusing on identifying and responding to emerging threats and opportunities linked to Infectious Diseases. We examine how AI tools can enhance signal…
Fake news has emerged as a critical global issue, magnified by the COVID-19 pandemic, underscoring the need for effective preventive tools. Leveraging machine learning, including deep learning techniques, offers promise in combatting fake…
A Collaborative Artificial Intelligence System (CAIS) is a cyber-physical system that learns actions in collaboration with humans in a shared environment to achieve a common goal. In particular, a CAIS is equipped with an AI model to…
Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the…
The COVID-19 pandemic has accelerated the implementation and acceptance of remotely proctored high-stake assessments. While the flexible administration of the tests brings forth many values, it raises test security-related concerns.…
Artificial Intelligence brings innovations into the society. However, bias and unethical exist in many algorithms that make the applications less trustworthy. Threats hunting algorithms based on machine learning have shown great advantage…
Accurate forecasts of COVID-19 is central to resource management and building strategies to deal with the epidemic. We propose a heterogeneous infection rate model with human mobility for epidemic modeling, a preliminary version of which we…
The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these demands cannot be effectively conducted without a nationwide…
We are witnessing a widespread adoption of artificial intelligence in healthcare. However, most of the advancements in deep learning in this area consider only unimodal data, neglecting other modalities. Their multimodal interpretation…
Since the appearance of Covid-19 in late 2019, Covid-19 has become an active research topic for the artificial intelligence (AI) community. One of the most interesting AI topics is Covid-19 analysis of medical imaging. CT-scan imaging is…
Crisis management is a complex problem raised by the scientific community currently. Decision support systems are a suitable solution for such issues, they are indeed able to help emergency managers to prevent and to manage crisis in…
Using machine learning algorithms for the rapid diagnosis and detection of the COVID-19 pandemic and isolating the patients from crowded environments are very important to controlling the epidemic. This study aims to develop a point-of-care…
The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is…