[MICCAI'2024, Oral] Official implementation of BrLP method from "Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge"
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Updated
Nov 19, 2024 - Python
[MICCAI'2024, Oral] Official implementation of BrLP method from "Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge"
Fast regression and mediation analysis of vertex or voxel MRI data with TFCE
Scikit-longitudinal (Sklong) is an open-source Python library & Scikit-Learn API compliant, tailored to longitudinal machine learning classification tasks. It is ideal for researchers, data scientists, and analysts, as it provides specialist tools for dealing with repeated-measures data challenges
Auto-Scikit-Longitudinal (Auto-Sklong) is an automated machine learning (AutoML) library designed to analyse longitudinal data (Classification tasks focussed as of today) using various search methods. Namely, Bayesian Optimisation via SMAC3, Asynchronous Successive Halving, Evolutionary Algorithms, and Random Search via GAMA
GWAS tools for longitudinal genetic traits based on fGWAS statistical model
Proactive methodological disclosure of a high resolution precision calibrated estimate of the Gompertz-Makeham Law of Mortality and general utilization hazard rates through lifespan interferometry against annual census data consolidated from the administrative data of all publicly funded healthcare provided in a single geopolitical jurisdiction.
R functions to generate lavaan code for testing longitudinal measurement invariance
Handling an Inconsistently Coded Categorical Variable in a Longitudinal Dataset
Handling an Inconsistently Coded Categorical Variable in a Longitudinal Dataset
Generalised joint models of survival and multivariate longitudinal data
scikit-lexicographical-trees: Based upon Scikit-Learn(-tree), it offers adapted trees and forest for Longitudinal Classification
An R-based Longitudinal mEtaGenomic Analysis Toolkit for microbiome data
Optimising the prediction of depression remission: A longitudinal machine learning approach
Analysis guide for IPUMS PMA longitudinal data
Hurricane Track Analysis via Sasaki-based Splines Models
GWAS tools for longitudinal genetic traits based on fGWAS statistical model
An R package for I-prior regression
A tool to visualize LACE output.
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