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rhenao-group's Projects

calibration_uncertainty_t2e

Calibration and Uncertainty in Neural Time-to-Event Modeling

cf_balancing

Counterfactual Regression with Balancing Weights

counterfactual_survival_analysis

Enabling Counterfactual Survival Analysis with Balanced Representations

Machine learning models for multi-organ, multi-disease prediction in chest CT volumes. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."

ct-volume-preprocessing

End-to-end Python CT volume preprocessing pipeline to convert raw DICOMs into clean 3D numpy arrays for ML. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."

dnmc

Repo for Disentangled Neural Mixture Cure Models

ecrt

Supercharging Imbalanced Data Learning WithCausal Representation Transfer

gradient-importance-learning

Gradient Importance Learning for Incomplete Observations, Gao et al., ICLR 2022

medgenetics

Mutation pathogenicity prediction for channelopathic and cardiomyopathic genes RYR2, KCNQ1, KCNH2, and SCN5A

pytorch-zoom-in-network

Efficient Classification of Very Large Images with Tiny Objects

relational-autoencoders

Learning Autoencoders with Relational Regularization

sarle-labeler

Automatic extraction of structured labels from radiology reports. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."

structured_latent_odes

Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations

survival_cluster_analysis

Survival Cluster Analysis

vie

Variational Disentanglement for Rare Event Modeling

vsi

Variational Survival Inference

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