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Helena Klara Jambor

Publications and source records attributed to Helena Klara Jambor.

3 recordsLinked to original sources

Patient-centered visualization of multistage cancer treatment trajectories

Effective communication of multistage cancer treatment trajectories remains a major challenge, particularly for patients with limited health literacy. We present a patient-centered visualization approach for representing complex, phase-based oncology treatments, integrating principles from information visualization, user experience (UX) design, and cognitive psychology. Using acute myeloid leukemia (AML) as a case study, we developed two timeline-based representations: a static, visually simplified trajectory emphasizing structure and hierarchy, and an interactive variant with layered information. We evaluated both approaches in a quantitative survey, measuring comprehension of treatment sequences, perceived confidence, and information quality. Results show that the static visualization significantly improves understanding and clarity, highlighting the importance of visual hierarchy, consistent encoding, and reduced complexity when communicating temporal medical processes compared to the baseline. In contrast, additional interactivity did not improve performance and introduced navigational overhead, suggesting that interaction must be carefully aligned with cognitive demands. Our findings contribute to visualization research by demonstrating how patient-centered design can improve the interpretability of multistage treatment trajectories. We derive design implications for temporal medical visualizations, emphasizing simplicity, structural clarity, and accessibility to support informed decision-making in clinical contexts.

cs.HC↗

From zero to figure hero. A checklist for designing scientific data visualizations

Biological research spans scales and methodologies, generating complex data visualizations such as images, text, numbers, networks, and maps. With increasingly large and multimodal datasets, effective visualization is essential for efficiently conveying scientific insights. Despite this crucial role, biologist often lack training in data visualization and information design. This work addresses this gap by providing a framework for creating clear, accurate, and impactful visualizations of biological data. It is centered around a checklist that guides biologists through the process of developing publishable figures. The guide and checklist cover key aspects such as selecting appropriate display types, using color palettes effectively, and optimizing figure layouts to communicate complex data. Additionally, the work is supported by evidence from visualization research, ensuring that the checklist recommendations are grounded in established principles. By following this guide, biologists can enhance their visual data presentations, ultimately increasing the impact of their scientific findings on diverse audiences.

cs.HC↗

Community-developed checklists for publishing images and image analysis

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality of microscopy data is in publications.

q-bio.OT↗