Code used in the Preoperative Surgical Risk Prediction project/paper

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.

Code and Datasets for the paper "Domain Knowledge Guided Deep Learning with Electronic Health Records", published on ICDM 2019.

Modular decision-support system for chronic condition self-management

Code and Datasets for the paper "Identifying Sepsis Subphenotypes via Time-Aware Multi-ModalAuto-Encoder", published on KDD 2020.

Electronic Health Record system for a children's clinic in Swaziland. Developed for Heart for Africa, a nonprofit organization.

Code and Datasets for the paper "Deconfounding actor-critic network with policy adaptation for dynamic treatment regimes", published on KDD 2022.

Code for ICHE 2018: A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers. https://doi.org/10.1017/ice.2018.16

PARALLEL AND DISTRIBUTED ELECTRONIC HEALTH RECORD MANAGEMENT SYSTEM

Code for the paper "Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning", published on ICDM 2021.

Rails API back-end for Theurgy. For use with JavaScript front-end.

comprehensive healthcare management platform connecting patients and doctors. Features include secure user authentication, detailed patient medical profiles, doctor specialization management, prescription tracking, medical history records, and appointment scheduling. Built with MongoDB for robust data storage and Node.js backend.

[BIBM 2025] Source code for "CafeMed: Causal Attention Fusion Enhanced Medication Recommendation".

My Master's Dissertation: Information Systems Architecture Definition for the Portuguese Electronic Health Record

💉 Dermatology EMR

One of the top solutions for The 2019 DII National Data Science Challenge: https://sbmi.uth.edu/dii-challenge/. More details in the paper "An interpretable deep-learning model for early prediction of sepsis in the emergency department", published on Patterns 2021.

Machine Learning to predict ARDS from Chest X-Ray images and Medical Data

Code for the paper "Temporal clustering with external memory network for disease progression modeling". Accepted by ICDM 2021.

Software suite which extracts key information from medical discharge summaries