Kamaleswaran-Lab/Clin-JEPA

🧪Yet Another ICU Benchmark: a holistic framework for the standardization of clinical prediction model experiments. Provide custom datasets, cohorts, prediction tasks, endpoints, preprocessing, and models. Paper: https://arxiv.org/abs/2306.05109

An interpretable foundation model of the patient clinical timeline: event forecasting, calibrated time-to-event alerts, and concept-level interpretability, benchmarked head-to-head against tuned GBMs, tabular foundation models, and survival baselines on MIMIC-IV, eICU, and GEMINI via the MEDS standard.

A customizable pipeline for multimodal data extraction from MIMIC-IV!

An open workbench for leakage-aware, calibrated, explainable risk modeling on longitudinal EHR-style data — built for students, labs, and health-informatics research.

MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases

Electronic Health Record Analysis with Python.

Machine learning and decision intelligence models designed to improve healthcare safety through clinical risk prediction and medical interaction analysis.

JEPA-Anything: Learning Predictive Models across Different Worlds