This project integrates data science and machine learning to advance medical diagosis and public health policies. Example projects:

1) Heart disease is the leading cause of death in the United States, and it affects Native Hawaiians and Pacific Islanders at a higher rate. The electrocardiogram (ECG) is an essential tool to evaluate patients with cardiac conditions such as irregular heartbeat, bradycardia, tachycardia, congenital and acquired heart defects, as well as cardiac manifestation of certain diseases, such as cancer, lupus, and infections. We propose to use a novel combination of algorithms and machine learning to detect heart disease such as Kawasaki disease from ECG. The goal of the project is to provide cardiologists with an additional tool for their diagnosis.

2) Epidemics such as COVID19 poses significant challenges to data analysis due to having many heterogeneous data sources, often captured at different time and geographic scales. Massive amount of data have been collected during COVID19 (ex. COVID-19 Data hub and C3 AI COVID19 data lake). The goal of this project is to learn how to clean/pre-process such data and to develop advance models of disease propagation.


Disease diagnosis with ECG

Descartes detects heart disease such as Kawasaki disease from ECG.

COVID19 Data Lake

COVID19 Data Lake

Descartes analyzes COVID19 data.