GitHub Repos developed for MACHAMP Lab Projects!
kidneydashboard: https://github.com/abbyjsun/kidneydashboard
Shows machine learning outputs
STARAPTOR-data-harmonization: https://github.com/AdvayMonga/STARAPTOR-data-harmonization
Machine learning pipeline for predicting kidney transplant outcomes across multi-site cohorts using batch harmonization
HierarchicalMogSampler.jl: https://github.com/HedwigNordlinder/HierarchicalMogSampler.jl
Focused Julia package for a two-component Gaussian mixture for repeated measurements within each subject, subject-specific component means, subject-specific component scale multipliers, component-shared covariance matrices across subjects, Gibbs sampling for the latent allocation stage only, work in progress by Hedwig et al.
GLAM.jl: https://github.com/HedwigNordlinder/GLAM.jl
Provides reproducible simulation for repeated-measurement paient data, train/test benchmark generation, end-to-end comparison between naive averaging and latent cluster-aware averaging, and pooled AUROC/AUPRC curves for both feature identification and patient-level classification, work in progress by Hedwig et al.
SOMSOS.jl: https://github.com/HedwigNordlinder/SOMSOS.jl
Implements the scalar-on-matrix spike-and-slab logistic regression from the GLAM.jl package, work in progress by Hedwig et al.
TEPIG: https://github.com/aleczzhang/TEPIG
Implements the novel aglorithm, TEnsor sparse grouP lasso with clusterInG (TEPIG), work in progress by Zhang et al.
Procurement-biopsy-pathomics-ml GitHub repository: https://github.com/jeremysrubin/procurement-biopsy-pathomics-ml/
Provides code and maodels for Rodrigues et al. (in preparation) for predicting kidney transplant recipient outcomes with machine learning methods that integrate procurement biopsy pathomics and clinical data
RIPR: https://github.com/jeremysrubin/RIPR
Implements the novel algorithm, ridge regression for functional form identification of continuous predictors (RIPR) in Rubin et al. (2022)