Building on the topic from june the focus is on visualising patient-level data (generated with AI)
There was a recently publication of a trial on treatment of patients with hyperkalemia. While the challenge in June was the improvement of the original plot the focus is now on the individual data.
Data set:
The data was created using AI-generated code matching the results shown in the plot of the publication. This prompt was used with Claude 4.
The Challenge:
This months challenge is a follow-up from last month. Generate a plot that includes patient level data information or distribution information.
Reference:
Sodium zirconium cyclosilicate versus sodium polystyrene sulfonate for treatment of hyperkalemia in hemodialysis patients: a randomized clinical trial The publication is available via NIH or BMC Nephrology.
A description of the challenge can also be found here.
A recording of the session can be found here.
Several visualisations are presented, where each is forming a part of a wider submission. This highlights how a series of data visualisations can be used to investigate and identify key relationships in the data, and then to subsequently highlight these key relationships when communicating findings.
The complete story from Thomas Weissensteiner can be found on his publication page.
The code and documentation is provided by Thomas Weissensteiner on his publication page
For attribution, please cite this work as
SIG (2025, July 9). VIS-SIG Blog: Wonderful Wednesday July 2025 (64). Retrieved from https://graphicsprinciples.github.io/posts/2025-07-09-wonderful-wednesday-july-2025/
BibTeX citation
@misc{sig2025wonderful, author = {SIG, PSI VIS}, title = {VIS-SIG Blog: Wonderful Wednesday July 2025 (64)}, url = {https://graphicsprinciples.github.io/posts/2025-07-09-wonderful-wednesday-july-2025/}, year = {2025} }