Medical Concept Annotation Tool

Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"

FEMR (Framework for Electronic Medical Records) provides tooling for large-scale, self-supervised learning using electronic health records

Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record

The official implementation of our paper "MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Learning" (TheWebConf 2023).

Building data processing pipelines for documents processing with NLP using Apache NiFi and related services

Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)

Functions to map between ICD-10 terms and PheCodes for UK Biobank hospital electronic health records

ACES: Automatic Cohort Extraction System for Event-Streams

Toolkit for a learning health system

Source code of ME2Vec.

RadioLOGIC: A general model for processing unstructured reports and making decisions in healthcare

Source code for the paper "Generating Synthetic Training Data for Supervised De-Identification of Electronic Health Records" in Future Internet (2021).

A set of tools for extracting formattable data from clinical notes stored in electronic health record systems.

Backend for a distributed electronic health records system

Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms

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.

Paper published in IEEE 33rd International Symposium on Computer Based Medical Systems (CBMS)

Repository for the journal article, 'Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things Application', Mahbub Ul Alam, Rahim Rahmani. Sensors 21, no. 15: 5025, https://doi.org/10.3390/s21155025.