DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow
[CVPR'25] Enhanced Contrastive Learning with Multi-view Longitudinal Data for Chest X-ray Report Generation
Scikit-Longitudinal (Sklong) your tailored (health) Longitudinal machine learning library built on top of Scikit-Learn
Multiple Frequency Estimation Under Local Differential Privacy in Python
Sequence-to-sequence image and contour prediction library for longitudinal datasets [PMB'23]
EchoTime: explainable structural similarity for time series and time-series datasets, with shareable HTML reports and agent-ready JSON.
[npj Digital Medicine] "Harnessing the power of longitudinal medical imaging for eye disease prognosis using Transformer-based sequence modeling" by Gregory Holste, Mingquan Lin, Ruiwen Zhou, Fei Wang, Lei Liu, Qi Yan, Sarah H Van Tassel, Kyle Kovacs, Emily Y Chew, Zhiyong Lu, Zhangyang Wang, & Yifan Peng
PyIOmica (pyiomica) is a Python package for omics analyses.
Repository for the EDBT'23 paper "Frequency Estimation of Evolving Data Under Local Differential Privacy".
Longitudinal Flow Matching for Trajectory Modeling (AISTAT 2026 Spotlight)
Federated time-dependent graph evolution prediction with missing timepoints.
A Python based graphical tool to preprocess tabular datasets
[ICML 2026] ARTIST: Adaptive Time Series Reasoning via Segment Selection
A comprehensive Python package for healthcare data engineering, designed to extract, transform, and feature engineer patient data from CogStack-based EHR datalakes. Enables patient-level aggregation, longitudinal time series construction (up to 25 years retrospective), flexiblefeature engineering (biochemistry, demographics, medications, diagnoses
Prior-fitted networks for time-series causal inference and longitudinal counterfactual outcome prediction.
This project applies Data Analysis using python libraries to a longitudinal dataset to explore the relationship between a child's age, expressive language skills, and their socialization development. A multilevel modeling approach is used to account for the correlated, repeated measurements taken from each child over several years.
Simulations for the cosinor model
Effectively visualizing cluster flows and sizes for sequential cluster analyses using matplotlib.
Framework for generating longitudinal synthetic populations from life-course trajectories.
Python version similar to R latrend for longitudinal trajectory clustering and visualization.
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