Publications (19)
Accelerated Stochastic Power Iteration
Christopher De Sa, Bryan He, Ioannis Mitliagkas +2
Principal component analysis (PCA) is one of the most powerful tools in machine learning. The simplest method for PCA, the power iteration, requires full-data pa…
SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals
Rahul Thapa, Bryan He, Magnus Ruud Kjaer +4
Sleep is a complex physiological process evaluated through various modalities recording electrical brain, cardiac, and respiratory activities. We curate a large polysomnography dat…
EchoPrime: A Multi-Video View-Informed Vision-Language Model for Comprehensive Echocardiography Interpretation
Milos Vukadinovic, Xiu Tang, Neal Yuan +5
Echocardiography is the most widely used cardiac imaging modality, capturing ultrasound video data to assess cardiac structure and function. Artificial intelligence (AI) in echocar…
Pretraining on Sleep Data Improves non-Sleep Biosignal Tasks
William Lehn-Schiøler, Magnus Ruud Kjær, Phillip Hempel +7
Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and disease risk prediction. In…
Medical Image De-Identification Benchmark Challenge
Linmin Pei, Granger Sutton, Michael Rutherford +67
The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particular…
Deep Learning Discovery of Demographic Biomarkers in Echocardiography
Grant Duffy, Shoa L. Clarke, Matthew Christensen +4
Deep learning has been shown to accurately assess 'hidden' phenotypes and predict biomarkers from medical imaging beyond traditional clinician interpretation of medical imaging. Gi…