Official implementation of TACCO (Task-guided Co-clustering).
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Updated
Jun 19, 2024 - Python
Official implementation of TACCO (Task-guided Co-clustering).
BERT style transformer model on CMS synthetic EHR data for diagnosis and procedure prediction in PyTorch.
This repository hosts a cutting-edge deep learning model developed to predict 6-month incident heart failure utilizing electronic health records (EHRs). Heart failure is a multifaceted medical condition characterized by its significant impact on patients' well-being and healthcare systems.
This research uncovers the increased suicide risk in men with mental illness post-hospitalization, analyzing 1.4M+ cases. It highlights the importance of targeted interventions based on identified risk factors.
COVID-19 EHR data analysis pipeline
HealthDatum is an electronic health record system that provides easy means of managing clinical data.
Tool for EHR & mutation profile based patient clustering & visualization, developed in partial fulfillment of the requirements for the course “Medical Informatics” at the University Medical Center Göttingen.
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks
CARE-ML: Predicting the use of restraint on psychiatric inpatients using EHRs and ML. Developed by sarakolding and signekb for their Master's Thesis.
attribute-based access control implementation for EHRs
KDD2020 paper; Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder
Collection of bio-medical and clinical ner models in spacy, stanza, flair with some utility files
In this project, we will create a deep learning model trained on EHR data (Electronic Health Records) to find suitable patients for testing a new diabetes drug.
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