相关论文: ESID: Exploring the Design and Development of a Vi…

In recent years, the use of expressive surface visualizations in the representation of vascular structures has gained significant attention. These visualizations provide a comprehensive understanding of complex anatomical structures and are…

The timely detection of disease outbreaks through reliable early warning signals (EWSs) is indispensable for effective public health mitigation strategies. Nevertheless, the intricate dynamics of real-world disease spread, often influenced…

We introduce our ongoing work toward an insight-based evaluation methodology aimed at understanding practitioners' mental models when exploring medical data. It is based on ParcoursVis, a Progressive Visual Analytics system designed to…

Visualisation is often presented as a means of simplifying information and helping people understand complex data. In this paper we describe the design, development and evaluation of an interactive visualisation for spreadsheet formulae…

Machine learning for data-driven diagnosis has been actively studied in medicine to provide better healthcare. Supporting analysis of a patient cohort similar to a patient under treatment is a key task for clinicians to make decisions with…

Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seldom enable explicit checks of the resulting interpretations…

Real-time monitoring and responses to emerging public health threats rely on the availability of timely surveillance data. During the early stages of an epidemic, the ready availability of line lists with detailed tabular information about…

Spatial analysis can generate both exogenous and endogenous biases, which will lead to ethics issues. Exogenous biases arise from external factors or environments and are unrelated to internal operating mechanisms, while endogenous biases…

In response to the COVID-19 pandemic and the potential threat of future epidemics caused by novel viruses, we developed a flexible framework for modeling disease intervention effects. This tool is intended to aid decision makers at multiple…

In this paper, a method to study how the design of indoor spaces and people's movement within them affect disease spread is proposed by integrating computer-aided modeling, multi-agent movement simulation, and airborne viral transmission…

We present here the proceedings of the 5th seminar on emerging infectious diseases (EIDs), held in Paris on March 22nd, 2016, with seven priority proposals that can be outlined as follows:$\bullet$Encourage research on the prediction,…

In this paper, we present an approach in the Multimodal Learning Analytics field. Within this approach, we have developed a tool to visualize and analyze eye movement data collected during learning sessions in online courses. The tool is…

Confronted by a rapidly evolving health threat, such as an infectious disease outbreak, it is essential that decision-makers are able to comprehend the complex dynamics not just in space but also in the 4th dimension, time. In this paper…

Constructing latent vector representation for nodes in a network through embedding models has shown its practicality in many graph analysis applications, such as node classification, clustering, and link prediction. However, despite the…

Appropriate evaluation and experimental design are fundamental for empirical sciences, particularly in data-driven fields. Due to the successes in computational modeling of languages, for instance, research outcomes are having an…

Epiabm is a fully tested, open-source software package for epidemiological agent-based modelling, re-implementing the well-known CovidSim model from the MRC Centre for Global Infectious Disease Analysis at Imperial College London. It has…

This paper describes an online tool for the visualization of medical emergency locations, randomly generated sample paths of medical emergencies, and the animation of ambulance movements under the control of various dispatch methods in…

The ability to effectively visualize data is crucial in the contemporary world where information is often voluminous and complex. Visualizations, such as charts, graphs, and maps, provide an intuitive and easily understandable means to…

Epidemic models are useful tools in the fight against infectious diseases, as they allow policy makers to test and compare various strategies to limit disease transmission while mitigating collateral damage on the economy. Epidemic models…

Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although previous works have shown the viability of using in silico testing for diagnosis, there is a…