(248) 635-2442

Applications:
Behavioral Science, Computer Science
Methodologies:
Algorithms, Artificial Intelligence, Deep Learning, Digital Data Curation, Machine Learning

Hamid Ghanbari

Assistant Professor

Internal Medicine

My research focuses on using digital health solutions, signal processing, machine learning and ecological momentary assessment to understand the physiological and psychological determinants of symptoms in patients with atrial fibrillation. I am building a research framework for rich data collection using smartphone apps, medical records and wearable sensors. I believe that creating a multidimensional dataset to study atrial fibrillation will yield important insights and serve as model for studying all chronic medical conditions.