Background | From electronic health records to state matrices | Load data and compute individual patient state matrices | Compute the Jaccard distance between patients | Analyse clusters and get sequences statistics
Package: MSCA 1.4.0
MSCA: Unsupervised Clustering of Multiple Censored Time-to-Event Endpoints
Provides basic tools and wrapper functions for computing clusters of instances described by multiple time-to-event censored endpoints. From long-format datasets, where one instance is described by one or more dated records, the main function, `make_state_matrices()`, creates state matrices. Based on these matrices, optimised procedures using the Jaccard distance between instances enable the construction of longitudinal typologies. The package is under active development, with additional tools for graphical representation of typologies planned. For methodological details, see our accompanying paper: `Delord M, Douiri A (2025) <doi:10.1186/s12874-025-02476-7>`.
Authors:
MSCA_1.4.0.tar.gz
MSCA_1.4.0.zip(r-4.7-x86_64)MSCA_1.4.0.zip(r-4.7-arm64)MSCA_1.4.0.zip(r-4.6-x86_64)MSCA_1.4.0.zip(r-4.6-arm64)MSCA_1.4.0.zip(r-4.5-x86_64)
MSCA_1.4.0.tgz(r-4.6-x86_64)MSCA_1.4.0.tgz(r-4.6-arm64)MSCA_1.4.0.tgz(r-4.5-x86_64)MSCA_1.4.0.tgz(r-4.5-arm64)
MSCA_1.4.0.tar.gz(r-4.7-arm64)MSCA_1.4.0.tar.gz(r-4.7-x86_64)MSCA_1.4.0.tar.gz(r-4.6-arm64)MSCA_1.4.0.tar.gz(r-4.6-x86_64)
MSCA_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MSCA/json (API)
| # Install 'MSCA' in R: |
| install.packages('MSCA', repos = c('https://marc-75.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/marc-75/msca/issues
Datasets:
- EHR - Description of the EHR dataset
Last updated from:dc4391b051. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 145 | ||
| linux-devel-x86_64 | OK | 200 | ||
| source / vignettes | OK | 295 | ||
| linux-release-arm64 | OK | 146 | ||
| linux-release-x86_64 | OK | 144 | ||
| macos-release-arm64 | OK | 175 | ||
| macos-release-x86_64 | OK | 327 | ||
| macos-oldrel-arm64 | OK | 194 | ||
| macos-oldrel-x86_64 | OK | 311 | ||
| windows-devel-arm64 | OK | 354 | ||
| windows-devel-x86_64 | OK | 154 | ||
| windows-release-arm64 | OK | 361 | ||
| windows-release-x86_64 | OK | 162 | ||
| windows-oldrel-x86_64 | OK | 160 | ||
| wasm-release | OK | 155 |
Exports:fast_clara_jaccardfast_jaccard_distget_cluster_sequencesmake_state_matricessequence_stats
Dependencies:clidata.tabledplyrfastkmedoidsgenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigR6RcppRcppArmadilloRcppParallelrlangtibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Description of the EHR dataset | EHR |
| Fast CLARA-like clustering using Jaccard dissimilarity - beta version - under assessment | fast_clara_jaccard |
| Compute upper triangle Jaccard distance | fast_jaccard_dist |
| Extract sequences of length k within clusters | get_cluster_sequences |
| Construct state matrices from longitudinal EHR Data | make_state_matrices |
| Compute sequence statistics | sequence_stats |