This publication details the development of an automated online system for assessing stroke risk, utilizing advanced algorithms for accurate predictions.
We present a research tool for users to take proactive steps in managing their health and helping healthcare professionals make informed clinical decisions.
This research offers a deployable, cost-effective, and standards-compliant solution for acute stroke monitoring with commodity wearable devices, providing a foundation for broader acute-care applications.
This open-source prototype presents a major step in assistive technologies for wheelchair users and critical care patients.
A chatbot designed to assess stroke risk using a conversational interface, integrating machine learning algorithms for personalized risk prediction.
Contributed to research projects focusing on biomedical data analysis and machine learning applications in healthcare.
Created a 24-week curriculum to educate and inspire Uyghur children and youth and train them in programming online and design prototyping.