Search the digital library catalog

Abstract: Background: Supporting and understanding the health of patients with chronic diseases and cardiovascular disease (CVD) risk is often a major challenge. Health data are often used in providing feedback to patients, and visualization plays an important role in facilitating the interpretation and understanding of data and, thus, influencing patients’ behavior. Visual analytics enable efficient analysis and understanding of large datasets in real time. Digital health technologies can promote healthy lifestyle choices and assist in estimating CVD risk. Objective: This review aims to present the most-used visualization techniques to estimate CVD risk. Methods: In this scoping review, we followed the Joanna Briggs Institute PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The search strategy involved searching databases, including PubMed, CINAHL Ultimate, MEDLINE, and Web of Science, and gray literature from Google Scholar. This review included English-language articles on digital health, mobile health, mobile apps, images, charts, and decision support systems for estimating CVD risk, as well as empirical studies, excluding irrelevant studies and commentaries, editorials, and systematic reviews. Results: We found 774 articles and screened them against the inclusion and exclusion criteria. The final scoping review included 17 studies that used different methodologies, including descriptive, quantitative, and population-based studies. Some prognostic models, such as the Framingham Risk Profile, World Health Organization and International Society of Hypertension risk prediction charts, Cardiovascular Risk Score, and a simplified Persian atherosclerotic CVD risk stratification, were simpler and did not require laboratory tests, whereas others, including the Joint British Societies recommendations on the prevention of CVD, Systematic Coronary Risk Evaluation, and Framingham-Registre Gironí del COR, were more complex and required laboratory testing–related results. The most frequently used prognostic risk factors were age, sex, and blood pressure (16/17, 94% of the studies); smoking status (14/17, 82%); diabetes status (11/17, 65%); family history (10/17, 59%); high-density lipoprotein and total cholesterol (9/17, 53%); and triglycerides and low-density lipoprotein cholesterol (6/17, 35%). The most frequently used visualization techniques in the studies were visual cues (10/17, 59%), followed by bar charts (5/17, 29%) and graphs (4/17, 24%). Conclusions: On the basis of the scoping review, we found that visualization is very rarely included in the prognostic models themselves even though technology-based interventions improve health care worker performance, knowledge, motivation, and compliance by integrating machine learning and visual analytics into applications to identify and respond to estimation of CVD risk. Visualization aids in understanding risk factors and disease outcomes, improving bioinformatics and biomedicine. However, evidence on mobile health’s effectiveness in improving CVD outcomes is limited.
Keywords: cardiovascular disease prevention, risk factors, visual analytics, visualization, mobile phone, PRISMA
Published in DKUM: 26.11.2024; Views: 0; Downloads: 1
Full text (435,60 KB)

Abstract: Tourists are flooded with advertising messages, including destination-attribute-based or user-imagery-based pictures, to persuade them to visit the destination. While research emphasizes destination choice to result from tourist-destination congruity, examining the influence different pictures have on tourist decision-making is of increasing interest. Therefore, this study sought to investigate the efficacy of destination-attribute-based versus user-imagery-based ad stimuli to influence the tourist-destination congruity and predict a person’s likelihood of choosing the destination. Results from a quantitative study of 496 young Slovenians show that a higher degree of ideal and ideal social tourist-destination congruence would lower one’s perceived purchase risk and yield positive attitudes toward the ad with a destination-attribute-based picture as opposed to the ad with a user-imagery-based picture. Implications for destination marketing are discussed, such as evaluating a typical destination visitor when one is included in the advertising and when one is not.
Keywords: congruity, advertising, marketing, tourist, picture, visualization
Published in DKUM: 10.10.2023; Views: 433; Downloads: 43
Full text (220,13 KB)
This document has many files! More...

Abstract: Algorithms make up a crucial part of computer science studies. Learning and understanding new algorithms can be quite interesting, but also hard and complex, especially for students. Visualization can significantly help with the understanding of the dynamic behaviour of algorithms by visually displaying each step of the algorithm, its purpose and how it changes the data. Besides faster and more efficient learning, the better understanding can also lead to potential algorithm improvements in the future. The goal of this thesis is visualization of the alpha-beta tree search algorithm for determining the next optimal move in a two-player, zero-sum, complete information game. The algorithm is visualized using two games, Tic-Tac-Toe and Othello. The algorithm operation can also be demonstrated using a custom tree with parameters chosen by the user.
Keywords: algorithm visualization, minimax algorithm, alpha-beta pruning, adversarial search
Published in DKUM: 08.11.2019; Views: 1262; Downloads: 78
Full text (1,52 MB)

Abstract: In recent years 3D modeling has been increasingly utilized during product design in lower secondary schools as well. Its greatest advantage over classical technical drawing and 2D drawing software lies in the fact students are able to observe the object they are designing from all the viewpoints of a virtual three-dimensional space. Since thinking and visualization in the process of object design also appear in three dimensions, the mental manipulation and guesswork required from students in order to add another dimension to an object pictured on a level plane are no longer necessary. Additionally, 3D modeling has a range of contributions to the cognitive development of children, which was also the subject of this research. The central question raised was whether students are able to improve their spatial ability by using modeling tools. The research included 196 students aged between 11-15 years, of which 95 were placed in the experimental group and 101 in the control group. Spatial ability was measured using pre-test and post-test.
Keywords: 3D modeling, cognitive development, spatial abilities, visualization
Published in DKUM: 15.12.2017; Views: 1334; Downloads: 155
Full text (681,51 KB)
This document has many files! More...

Keywords: cosmological visualization, cosmological datasets, geometric algorithms, data preprocessing, octree volume, frustum culling
Published in DKUM: 01.06.2012; Views: 1791; Downloads: 45
Link to full text