Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data

Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)

[ICASSP 2025 Oral] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

[ICASSP 2025 Oral] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

Patient-Level Analysis of Single Cell Disease Atlas with Optimal Transport of Gaussian Mixtures Variational Autoencoders

Official code for Learning Temporally Equivariance for Degenerative Disease Progression in OCT by Predicting Future Representations (MICCAI'24)

MARIO Challenge MICCAI 2024

Diabetes Progression in Electronic Health Records

Overview of DS, Classification Tree, Regression Tree, Logistic Regression, Multiple Linear Regression, Random Forest Classifiers, p-value approach to Decision Tree, Disease Progression Models, Neural Networks and Deep Learning.

Analysing CSF biomarkers and APOE4 effects on late-onset AD characterisation based on age, sex, cognitive scores, CSF biomarkers, and apoe4 status of 213 patients obtained from https://doi.org/10.34810/data614

A research framework for longitudinal EHR sequence modeling, exploring multiple temporal representations, learning objectives, and model classes for disease progression, survival analysis, and temporal phenotyping under censoring and irregular follow-up.

This repository contains python code which relates to this paper: Hyperbolic Embedding and Acoustic-based Learning for Topological Hierarchies in Parkinson’s Disease