Bobak J. Mortazavi

Self-Damaging Contrastive Learning

2021 · arXiv (Cornell University)

The recent breakthrough achieved by contrastive learning accelerates the pace for deploying unsupervised training on real-world data applications. However, unlabeled data in reality is commonly imbalanced and shows a long-tail distribution, and it is unclear …

Prediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures

2017 · IEEE Journal of Biomedical and Health Informatics

Electronic health records (EHR) provide opportunities to leverage vast arrays of data to help prevent adverse events, improve patient outcomes, and reduce hospital costs. This paper develops a postoperative complications prediction system by extracting data …