longitudinal-analysis

Extended Joint Models for Longitudinal and Survival Data

A 3D Attention U-Net model is developed, aimed at segmenting and tracking Multiple Sclerosis lesions in MRI images.

Supplementary materials for the manuscript "Clustering of longitudinal data: A tutorial on a variety of approaches" by N. G. P. Den Teuling, S.C. Pauws, and E.R. van den Heuvel (2026)

Early Life Microbiome Toolbox

Depth video data-enabled predictions of longitudinal dairy cow body weight using thresholding and Mask R-CNN algorithms

LAVA: Longitudinal Analysis of Viral Alleles

Supplementary materials for the manuscript "A comparison of methods for clustering longitudinal data with slowly changing trends" by N. G. P. Den Teuling, S.C. Pauws, and E.R. van den Heuvel, published in Communications in Statistics - Simulation and Computation (2021).

MARIO Challenge MICCAI 2024

Datasets and artifacts for the paper "A Longitudinal Analysis of Bloated Java Dependencies"

MetaboDynamics: a framework of probabilistic models to analyze longitudinal metabolomics data

`mbtransfer` is an R package for modeling microbiome dynamics. It provides functions for fitting transfer function models, simulating counterfactual trajectories, and selecting significantly perturbed taxa using mirror statistics.

List of software packages for repeated measures analysis in -omics data

Tracking how professional CS2 settings evolve over time through reproducible longitudinal data collection and analysis.

Early Growth Genetics Longitudinal Analysis.

Source code for "Learning accurate rigid registration for longitudinal brain MRI from synthetic data", presented at ISBI 2025.

Healthcare AI project analyzing migraine treatment outcomes using longitudinal statistical models in R.

Matching Methods for Time-Varying Observational Studies, in R

Positivity violations in marginal structural survival models with time-dependent confounding: a simulation study on IPTW-estimator performance.

Scripts related to "Associations between attention-deficit hyperactivity disorder (ADHD) symptom remission and white matter microstructure: A longitudinal analysis"

The Framingham Heart Study dataset (frmgham6.csv) offers vital insights into the risk factors associated with mortality. Using machine learning models for analysis: Logistic Regression, Random Forest and XGBoost, identification of several key predictors of death have been unearthed in this report.