Publications & Outputs

Digital Twin (DT) technology has emerged as a transformative approach in healthcare, but its application in personalized patient care remains limited. We introduce a general DT framework for personalized care planning (DT4PCP), with the core components being a real-time virtual representation of a patient's health and emerging predictive models to enable adaptive, personalized care. We implemented the DT4PCP framework for managing Type 2 Diabetes (DT4PCP-T2D), enabling real-time collection of behavioral data from patients with T2D, predicting emergency department (ED) risks, simulating the effects of different interventions, and personalizing care strategies to reduce ED visits.

Over 30 million Americans are affected by Type II diabetes (T2D), a treatable condition with significant health risks. This study aims to develop and validate predictive models using machine learning (ML) techniques to estimate emergency department (ED) visits among patients with T2D. Ensemble Learning and Random Forest models demonstrated superior predictive performance in terms of discrimination, calibration, and clinical applicability.

Cybersecurity training for health professionals is important for different stakeholders in healthcare. This project aims to shed light on the current landscapes of cybersecurity training in CAHIIM-accredited programs in Health information management (HIM) and health informatics using natural language processing (NLP). The research identifies trends in cybersecurity education within healthcare, emphasizing the integration of privacy and security measures in academic programs.

Health informatics education is an essential part of global health. However, the available health informatics programs across the globe are unequal. This study aims to identify the current state of health informatics education in Low- or Middle-Income Countries, focusing on Africa and Southeast Asia. We found most health informatics related education only exist in the USA, while in the other countries little to no education exists related to health informatics.

This study explores the influence of social determinants of health on emergency department visits by patients with diabetes and hypertension, contributing to understanding healthcare utilization patterns among chronic disease patients.