Data Science for Health

Data science provides excellent tools for health professionals to gain valuable knowledge from patient information and dataset. At the D2K Lab, students have the opportunity to work on projects sponsored by medical centers, researchers and health solution companies to tackle various topics of the industry, such as ECGs, preventive modeling, imaging analytics, and diagnostic accuracy, etc. 

Beat-to-beat Classification of Unlabeled ECGs in Adult Populations

 

Team Members: Alvin Magee, Anthony Chen, Xinyue Cui, Nicole Tan

ECG machines collect hours of data on patient heart activity each day, and doctors often do not have time to analyze all the data. Our goal is to process all the data and tag abnormalities for doctors to review.

Sponsor: Medical Informatics Corp.

Sponsor Mentor: Raajen Patel, Craig Rusin, Jamie Waugh, Vicken Asadourian

D2K Fellow: Randall Balestriero


Pediatric Cardiac ICU Arrhythmias Detection

Team Members: Robert Chen, Yanwan Dai, Yerin Han, Anirudh Kuchibhatla, Mario Paciuc, and Xin Tan

We develop a novel semi-supervised classification algorithm that detects JET, a lethal heart condition, in real-time by analyzing morphologies and features of the electrocardiogram and central venous pressure signals. This algorithm eliminates alarm fatigue and saves more children who suffer from arrhythmia.

Sponsor: Texas Children’s Hospital

Sponsor Mentor: Dr. Parag Jain and Raajen Patel

D2K Fellow: Souptik Barua

Faculty Mentor: Dr. Craig Rusin


Inferring Genomic Signatures in Age-Related Macular Degeneration Across Different Stages

Team Members: Yu Wu, Shryans Goyal, Zishi Wang, Minjun Park, Zach Moxley

We predict the importance of certain genes that are responsible for AMD across different stages. Using those genes, we analyze gene networks to give better information to doctors to find an effective cure for AMD which currently does not exist.

Sponsor: Baylor College of Medicine

Sponsor Mentor: Dr. Rinki Ratnapriya

D2K Fellow: Emma Zohner