We included the code to obtain the results reported in the study below:

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)

Used machine learning in R to assess individual variables involved in the intra-operative pathology consultation process.

Electronic Health Record Analysis using SQLite

This project aims to make predictions of stroke cases based on simple health data. Supervised machine learning algorithm was used after processing and analyzing the data. The model has predicted Stroke cases with 92.00% of sensitivity.

This pilot project deploys a supplemental OMOP table to map external measures of rurality (RUCC and RUCA).

ABP Imputation with EHR medication data is the second version of the ABP Imputer model.

EHR DREAM Challenge: Patient Mortality Prediction Submission. "moore" team submission

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

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 is implementation of my Masters thesis work and aims at predicting the patient mortality from the MIMIC-III v1.4 Database

OpenAPI which maps custom EHRs into FHIR R4 Patient and Observation resources. Other resources were not implemented (yet).

Data challenge from Holmusk to compare the risk of bleeding between two treatments using EHR extracted data.

For fully integrated EHR for the future

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.

Eases access to Caboodle data warehouse from Epic Electronic Health Record

Predict patients who are likely to be in the hospital for at-least 5-7 days

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.

The monolithic server-side repository of EHRoute, a secure Electronic Health Records (EHR) storage and sharing solution

CARE-ML: Predicting the use of restraint on psychiatric inpatients using EHRs and ML. Developed by sarakolding and signekb for their Master's Thesis.