98%
921
2 minutes
20
Data visualization tools have the potential to support decision-making for public health professionals. This review summarizes the science and evidence regarding data visualization and its impact on decision-making behavior as informed by cognitive processes such as understanding, attitude, or perception.An electronic literature search was conducted using six databases, including reference list reviews. Search terms were pre-defined based on research questions.Sixteen studies were included in the final analysis. Data visualization interventions in this review were found to impact attitude, perception, and decision-making compared to controls. These relationships between the interventions and outcomes appear to be explained by mediating factors such as perceived trustworthiness and quality, domain-specific knowledge, basic beliefs shared by social groups, and political beliefs.Visualization appears to bring advantages by increasing the amount of information delivered and decreasing the cognitive and intellectual burden to interpret information for decision-making. However, understanding data visualization interventions specific to public health leaders' decision-making is lacking, and there is little guidance for understanding a participant's characteristics and tasks. The evidence from this review suggests positive effects of data visualization can be identified, depending on the control of confounding factors on attitude, perception, and decision-making.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/17538157.2021.1982949 | DOI Listing |
Target Oncol
September 2025
Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
Background: Population pharmacokinetic models can potentially provide suggestions for an initial dose and the magnitude of dose adjustment during therapeutic drug monitoring procedures of imatinib. Several population pharmacokinetic models for imatinib have been developed over the last two decades. However, their predictive performance is still unknown when extrapolated to different populations, especially children.
View Article and Find Full Text PDFJ Am Chem Soc
September 2025
Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou 215123, Jiangsu P. R. China.
Advances in molecular analysis and characterization techniques should revolutionize the methods for scientific exploration across physics, chemistry, and biology, fundamentally overturning our understanding of interactions and processes that govern molecular behavior at the microscopic level. Currently, the absence of a molecular analysis method that can both quantify molecules and achieve single-molecule spatial resolution hinders our study of complex molecular systems in sorption and catalysis. Here, we propose a quantitative analysis strategy for small molecules confined in ZSM-5, a zeolite material extensively used in catalysis and gas separation, based on low-dose transmission electron microscopy.
View Article and Find Full Text PDFOper Neurosurg
September 2025
Department of Neurosurgery and the Training Base of Neuroendoscopic Physicians under the Chinese Medical Doctor Association, Jiangsu Clinical Medicine Center of Tissue Engineering and Nerve Injury Repair, Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, China.
Background And Objectives: Microvascular decompression (MVD) for hemifacial spasm (HFS) is commonly conducted under a microscope. We report a large series of fully endoscopic MVDs for HFS and describe our initial experience with 3-dimensional (3D) endoscopy.
Methods: Clinical data of 204 patients with HFS who underwent fully endoscopic MVD using 2-dimensional (2D) and 3D endoscopy (191 and 13 patients, respectively) from July 2017 to October 2024 were retrospectively analyzed.
mSystems
September 2025
Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Genome-scale metabolic models (GEMs) are widely used in systems biology to investigate metabolism and predict perturbation responses. Automatic GEM reconstruction tools generate GEMs with different properties and predictive capacities for the same organism. Since different models can excel at different tasks, combining them can increase metabolic network certainty and enhance model performance.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
School of Information Science and Automation, Northeastern University, Shenyang, 110819 China.
Accurate prediction of drug-target interactions (DTIs) is crucial for improving the efficiency and success rate of drug development. Despite recent advancements, existing methods often fail to leverage interaction features at multiple granular levels, resulting in suboptimal data utilization and limited predictive performance. To address these challenges, we propose CF-DTI, a coarse-to-fine drug-target interaction model that integrates both coarse-grained and fine-grained features to enhance predictive accuracy.
View Article and Find Full Text PDF