A software toolkit for the interconversion of standard data models for phenotypic data

A deep learning project predicting hyperinflammatory syndrome among COVID-19 patients using EHR data.

BERT model on CMS synthetic EHR data for diagnosis and procedure prediction in PyTorch

omopcept : an R package to access OMOP conCEPTs (all pros, no cons!) and flexible tidyverse compatible R functions for querying.

Discovering healthcare insights through data-driven analysis of EHRs. This project comprises three subprojects: data cleaning & preparation, exploratory data analysis and lastly, predictive modeling for in-hospital mortality and clinical risk stratification.

R package for cleaning anthropometric (height and weight) data from electronic health record systems.

Official implementation of TACCO (Task-guided Co-clustering).

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.

Identifying which patients to include or exclude from the clinical trials of a new diabetes drug based on predicted hospitalization time given by a machine learning regression model

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

This repo contains demonstration code to illustrate the use of the FIHR standard for healthcare data, developed by the HL7 organisation.

HealthDatum is an electronic health record system that provides easy means of managing clinical data.

Welcome to the Federated Learning for Rare Genetic Disorder Classification project! This repository demonstrates the application of Federated Learning (FL) techniques to classify rare genetic disorders using Electronic Health Record (EHR) data while addressing two critical challenges: privacy and limited data availability.

The MedTimeline library aims to provide a standardised process for pre-processing and generating patient journey timelines for the cardiology EHR dataset. Developed by Louise Rigny (Great Ormond Street Hospital for Children)

IPEHR-gateway is a solution to provide benefits of decentralized architecture to common HMS apps using standard APIs. IPEHR gateway is used to encrypt and decrypt passing data, support AQL queries of encrypted data and manage user’s cryptographic keys.

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.

COVID-19 EHR Benchmark - Online Platform

Eases access to Caboodle data warehouse from Epic Electronic Health Record

Pipeline for building Machine Learning Classifiers for the diagnosis of EHR text-data. We used this pipeline for our study, published here: https://doi.org/10.2196/23930.