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.
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.
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Jun 16, 2022
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