- UCLA Bioengineering
Office: 924 Westwood Blvd, Suite 420, Room P
Yiwen Meng is a PhD Student in Medical Imaging Informatics (MII) Group with Bioengineering deparrtment of University of Carlifornia, Los Angeles (UCLA). He is also the Graduate Student Reseacher in Radiological Science of UCLA.His main research interest is using data collected by wearable electronic devices and patient's electronic health record (EHR) to predict and diagnose physical and mental symptoms or diseases. Right now, he is working on applying discrete Hidden Markov Model (HMM) to predict patient's health status by data collected from Fitbit for patients with ischemic heart disease. He has built up theoretical background in statistical machine learning, deep learning as well as hardware development for non-invasive biomedical devices. He also serves as a reviewer for several journals like IEEE Transaction on biomedical circuits and systems. Before coming to UCLA, he obtained his BS and MS degree in Elecitrical Engineering at Iowa State Univerisity in 2014 and 2015, respectively.
- Meng Y, Speier W, Dzubur E, Spiegel B, Arnold C. Predicting Patient Health Status using Activity Tracker Data. Proceedings of the 2018 American Medical Informatics Association Annual Symposium. San Francisco; 2018. PDF