ThunderbornSakana/PyTorch-Implementation-of-Models-Based-on-Longitudinal-EHR-Data

PyTorch implementation of state-of-the-art deep learning models for learning patient representations from sequential EHR data.

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Experimental

This project helps healthcare researchers and data scientists use advanced AI models to analyze patient health records. It takes in longitudinal electronic health records (EHR) data, like the MIMIC-III dataset, and processes it to create patient representations. The output helps predict future diagnoses or mortality, enabling better risk assessment and clinical decision support.

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Use this if you are a healthcare researcher or data scientist needing to apply state-of-the-art deep learning models to predict patient outcomes from historical EHR data.

Not ideal if you are looking for a plug-and-play clinical prediction tool ready for direct patient care, as this is a research implementation for model development.

healthcare-analytics clinical-prediction electronic-health-records medical-research patient-risk-assessment
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 13 / 25

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Last pushed

Jun 16, 2022

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