Skip to main content
Have a personal or library account? Click to login
LongitProgression: A Python Tool for Studying Factors of Disease Progression through Multivariate Longitudinal Clustering Cover

LongitProgression: A Python Tool for Studying Factors of Disease Progression through Multivariate Longitudinal Clustering

Open Access
|Nov 2025

Figures & Tables

Figure 1

LongitProgression packages diagrams.

Figure 2

LongitProgression pipeline, from data load to final plots.

Listing 1

Longitudinal Clustering.

Figure 3

Creatinine and Potassium values over ten time points for Patient 10006.

Figure 4

Preparatory steps for performing longitudinal clustering analysis.

Figure 5

Progression of clinical markers for the three clusters

Figure 6

Significance matrices showing the statistical difference among the 3 clusters for Creatinine and Potassium at time points 2 and 8.

DOI: https://doi.org/10.5334/jors.603 | Journal eISSN: 2049-9647
Language: English
Submitted on: Jul 25, 2025
Accepted on: Sep 5, 2025
Published on: Nov 19, 2025
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Patrizia Ribino, Giovanni Paragliola, Claudia Di Napoli, Maria Mannone, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.